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#deeplearning #neuralnetworks
The transp ose of a matrix pro duct has a simple form: \((AB)^{T} = B^{T}A^{T}\) . (2.9) This allo ws us to demonstrate equation , b y exploiting the fact that the v alue 2.8 of suc h a pro duct is a scalar and therefore equal to its o wn transp ose:\( x^Ty = (x^Ty)^T = y^T x\)
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#deeplearning #neuralnetworks
W e can now solve equation Ax = b by the following steps:
1. A-1Ax = A−1b
2. Inx = A−1b
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#bayes #programming #r #statistics
The “evidence” for the model, p(D), is the overall probability of the data according to the model, determined by averaging across all possible parameter values weighted by the strength of belief in those parameter value
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#matlab #programming
The residual r=A*x-b is now r= -0.3333 -0.3333 0.3333 What happens in this case is that MATLAB produces the least squares best fit. This is the value of x which makes the magnitude of r, i.e., r(1) 2 + r(2) 2 + r(3)2 , as small as possible.
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#bayes #programming #r #statistics
The space of possibilities is the joint parameter space involving all combinations of parameter values. If we represent each parameter with a comb of, say, 1,000 values, then for P parameters there are 1,000 P combinations of parameter values.
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#deeplearning #neuralnetworks
The L 1 norm is commonly used in machine learning when the difference b etw een zero and nonzero elements is v ery imp ortan t. Every time an element of x mo v es a w a y from 0 by \(\epsilon\), the L 1 norm increases b y \(\epsilon\).
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#deeplearning #neuralnetworks
T o compute diag(v)x , we only need to scale each element xi b y vi . In other w ords, diag(v)x = \(x\cdot y\)
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#deeplearning #neuralnetworks
A unit vector is a vector with unit norm ||x||2 = 1
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#deeplearning #neuralnetworks
A vector x and a vector y are orthogonal to each other if xTy = 0 .
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#deeplearning #neuralnetworks
An eigenvector of a square matrix A is a non-zero vector v suc h that m ulti- plication b y A alters only the scale of v: Av = λv
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#deeplearning #neuralnetworks
Av= λv
The scalar λ is kno wn as the eigen v alue corresp onding to this eigenv ector. (One can also find a left eigen v ector suc h that v A = λ v , but we are usually concerned with righ t eigenv ectors
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#deeplearning #neuralnetworks
SVD of A = UVDT

The elemen ts along the diagonal of D are kno wn as the singular v alues of the matrix A . The columns of U are known as the left-singular v ectors . The columns of V are kno wn as as the right-singular v ectors
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#deeplearning #neuralnetworks
W e can actually interpret the singular v alue decomp osition of A in terms of the eigendecomposition of functions of A . The left-singular v ectors of A are the eigen v ectors of AAT . The righ t-singular v ectors of A are the eigen vectors of ATA . The non-zero singular v alues of A are the square ro ots of the eigen v alues of ATA . The same is true for AAT
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#bayes #programming #r #statistics
In other words, the normalizer for the beta distribution is the beta function \(B(a,b) = \int d\theta \space \theta^{a-1}(1-\theta)^{b-1}\)
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#bayes #programming #r #statistics
In R, beta(θ|a, b) is dbeta(θ,a,b),and B(a, b) is beta(a,b)
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#bayes #programming #r #statistics
The standard deviation of the beta distribution is \(\sqrt{μ(1 − μ)/(a + b +1)}\). Notice that the standard deviation gets smaller when the concentration κ = a + b gets larger.
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Article 1482331131148



This may be [...]



Waste management or Waste disposal is all the activities and actions required to manage waste from its inception to its final disposal.[1] This includes amongst other things, collection, transport, treatment and disposal of waste together with monitoring and regulation. It also encompasses the legal and regulatory framework that relates to waste management encompassing guidance on recycling etc.
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Waste management - Wikipedia
s. Unsourced material may be challenged and removed. (May 2011) (Learn how and when to remove this template message) [imagelink] Waste management in Kathmandu, Nepal [imagelink] Waste management in Stockholm, Sweden <span>Waste management or Waste disposal is all the activities and actions required to manage waste from its inception to its final disposal. [1] This includes amongst other things, collection, transport, treatment and disposal of waste together with monitoring and regulation. It also encompasses the legal and regulatory framework that relates to waste management encompassing guidance on recycling etc. The term normally relates to all kinds of waste, whether generated during the extraction of raw materials, the processing of raw materials into intermediate and final products, the co




Flashcard 1483106028812

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An [...] is the com bination of an enco der function that con v erts the input data into a differen t representation, and a deco der function that conv erts the new representation back into the original format
Answer
autoenco der

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An autoenco der is the com bination of an enco der function that con v erts the input data into a differen t representation, and a deco der function that conv erts the new representation back into the o

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Flashcard 1483107601676

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#deeplearning #neuralnetworks
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An autoenco der is the com bination of an [...], and a deco der function that conv erts the new representation back into the original format
Answer
enco der function that con v erts the input data into a differen t representation

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An autoenco der is the com bination of an enco der function that con v erts the input data into a differen t representation, and a deco der function that conv erts the new representation back into the original format

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Flashcard 1483109174540

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#deeplearning #neuralnetworks
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An autoenco der is the com bination of an enco der function that con v erts the input data into a differen t representation, and a [...]
Answer
deco der function that conv erts the new representation back into the original format

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An autoenco der is the com bination of an enco der function that con v erts the input data into a differen t representation, and a deco der function that conv erts the new representation back into the original format

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Flashcard 1483110747404

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#matlab #programming
Question
[...] determinant.
Answer
det

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det determinant.

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Flashcard 1483112320268

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#matlab #programming
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det [...]
Answer
determinant.

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det determinant.

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Flashcard 1483113893132

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#matlab #programming
Question
[...] eigenvalue decomposition
Answer
eig

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eig eigenvalue decomposition

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Flashcard 1483115465996

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#matlab #programming
Question
eig [...]
Answer
eigenvalue decomposition

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eig eigenvalue decomposition

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Flashcard 1483117038860

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#matlab #programming
Question
[...] singular value decomposition
Answer
svd

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svd singular value decomposition

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Flashcard 1483118611724

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#matlab #programming
Question
svd [...]
Answer
singular value decomposition

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svd singular value decomposition

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Flashcard 1483120184588

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#biochem #biology #cell
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The piecing together of the complete [...] pathway in the 1930s was a major triumph of biochemistry
Answer
glycolytic

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The piecing together of the complete glycolytic pathway in the 1930s was a major triumph of biochemistry

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Flashcard 1483121757452

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#biochem #biology #cell
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The piecing together of the complete glycolytic pathway in the [...] was a major triumph of biochemistry
Answer
1930s

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The piecing together of the complete glycolytic pathway in the 1930s was a major triumph of biochemistry

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Flashcard 1483123330316

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#biochem #biology #cell
Question
Two central reactions in glycolysis (steps 6 and 7) convert the [...] into 3-phosphoglycerate (a carboxylic acid; see Panel 2–8, pp. 104–105), thus oxidizing an aldehyde group to a carboxylic acid group.
Answer
three-carbon sugar inter- mediate glyceraldehyde 3-phosphate (an aldehyde)

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Two central reactions in glycolysis (steps 6 and 7) convert the three-carbon sugar inter- mediate glyceraldehyde 3-phosphate (an aldehyde) into 3-phosphoglycerate (a carboxylic acid; see Panel 2–8, pp. 104–105), thus oxidizing an aldehyde group to a carboxylic acid group.

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Flashcard 1483124903180

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#biochem #biology #cell
Question
Two central reactions in glycolysis (steps 6 and 7) convert the three-carbon sugar inter- mediate glyceraldehyde 3-phosphate (an aldehyde) into [...]; see Panel 2–8, pp. 104–105), thus oxidizing an aldehyde group to a carboxylic acid group.
Answer
3-phosphoglycerate (a carboxylic acid

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Two central reactions in glycolysis (steps 6 and 7) convert the three-carbon sugar inter- mediate glyceraldehyde 3-phosphate (an aldehyde) into 3-phosphoglycerate (a carboxylic acid; see Panel 2–8, pp. 104–105), thus oxidizing an aldehyde group to a carboxylic acid group.

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Flashcard 1483126476044

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#biochem #biology #cell
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In step 6, the enzyme [...] couples the energetically favorable oxidation of an aldehyde to the energetically unfavorable formation of a high-energy phosphate bond. At the same time, it enables energy to be stored in NADH. The formation of the high-energy phosphate bond is driven by the oxidation reaction, and the enzyme thereby acts like the “paddle wheel” coupler
Answer
glyceraldehyde 3-phosphate dehydrogenase

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In step 6, the enzyme glyceraldehyde 3-phosphate dehydrogenase couples the energetically favorable oxidation of an aldehyde to the energetically unfavorable formation of a high-energy phosphate bond. At the same time, it enables energy to be s

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Flashcard 1483128048908

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#biochem #biology #cell
Question
In step 6, the enzyme glyceraldehyde 3-phosphate dehydrogenase couples [...]. At the same time, it enables energy to be stored in NADH. The formation of the high-energy phosphate bond is driven by the oxidation reaction, and the enzyme thereby acts like the “paddle wheel” coupler
Answer
the energetically favorable oxidation of an aldehyde to the energetically unfavorable formation of a high-energy phosphate bond

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In step 6, the enzyme glyceraldehyde 3-phosphate dehydrogenase couples the energetically favorable oxidation of an aldehyde to the energetically unfavorable formation of a high-energy phosphate bond. At the same time, it enables energy to be stored in NADH. The formation of the high-energy phosphate bond is driven by the oxidation reaction, and the enzyme thereby acts like the

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Flashcard 1483129621772

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W e use the [...] sign to index the complement of a set.
Answer

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W e use the sign to index the complement of a set. F or example x − 1 is the v ector con taining all elemen ts of x except for x 1 , and x − S is the v ector con taining all of the elements of exce

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#deeplearning #neuralnetworks
W e can identi fy all of the n um b ers with v ertical co ordinate i b y writing a “ ” for the horizontal
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W e can identi fy all of the n um b ers with v ertical co ordinate i b y writing a “ ” for the horizontal : co ordinate. F or example, A i, : denotes the horizon tal cross section of A with v ertical co ordinate i

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Flashcard 1483133553932

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The transp ose of a matrix is [...]
Answer
the mirror image of the matrix across a diagonal line, called the main diagonal , running do wn and to the righ t, starting from its upp er left corner.

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The transp ose of a matrix is the mirror image of the matrix across a diagonal line, called the main diagonal , running do wn and to the righ t, starting from its upp er left corner.

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Flashcard 1483137223948

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Question
Note that the standard pro duct of tw o matrices is just a matrix con taining not the pro duct of the individual elements. Suc h an op eration exists and is called the [...] , and is denoted as . A
Answer
elemen t-wise pro duct Hadamard pro duct or

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Note that the standard pro duct of tw o matrices is just a matrix con taining not the pro duct of the individual elements. Suc h an op eration exists and is called the elemen t-wise pro duct Hadamard pro duct or , and is denoted as . A

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Flashcard 1483138796812

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#deeplearning #neuralnetworks
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Is the dot pro duct b etw een tw o v ectors comm utativ e?
Answer
Yes

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the dot pro duct b etw een tw o v ectors is comm utativ e: x y y = x

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Flashcard 1483144826124

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Question
The transp ose of a matrix pro duct has a simple form [...] (2.9) This allo ws us to demonstrate equation , b y exploiting the fact that the v alue 2.8 of suc h a pro duct is a scalar and therefore equal to its o wn transp ose:\( x^Ty = (x^Ty)^T = y^T x\)
Answer
simple form: \((AB)^{T} = B^{T}A^{T}\) .

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The transp ose of a matrix pro duct has a simple form: \((AB)^{T} = B^{T}A^{T}\) . (2.9) This allo ws us to demonstrate equation , b y exploiting the fact that the v alue 2.8 of suc h a pro duct is a scalar and therefore equal to its o wn transp ose:\( x^Ty = (x^Ty)^T

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Flashcard 1483147185420

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Question
W e can now solve equation Ax = b by the following steps:

[...]
Answer
1. A-1Ax = A−1b
2. Inx = A−1b

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W e can now solve equation Ax = b by the following steps: 1. A -1 Ax = A −1 b 2. I n x = A −1 b

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Flashcard 1483148758284

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#biochem #biology #cell
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fatty acids enter the bloodstream, where they bind to the abundant blood protein, [...]
Answer
serum albumin.

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fatty acids enter the bloodstream, where they bind to the abundant blood protein, serum albumin.

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Flashcard 1483150331148

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#biochem #biology #cell
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In addition to three molecules of NADH, each turn of the cycle also produces one molecule of [...] from FAD (see Figure 2–39), and one mol- ecule of the ribonucleoside triphosphate GTP from GDP
Answer
FADH 2 (reduced flavin adenine dinucleotide)

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In addition to three molecules of NADH, each turn of the cycle also produces one molecule of FADH 2 (reduced flavin adenine dinucleotide) from FAD (see Figure 2–39), and one mol- ecule of the ribonucleoside triphosphate GTP from GDP

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Flashcard 1483151904012

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#biochem #biology #cell
Question
In addition to three molecules of NADH, each turn of the cycle also produces one molecule of FADH 2 (reduced flavin adenine dinucleotide) from FAD (see Figure 2–39), and one mol- ecule of the [...]
Answer
ribonucleoside triphosphate GTP from GDP

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In addition to three molecules of NADH, each turn of the cycle also produces one molecule of FADH 2 (reduced flavin adenine dinucleotide) from FAD (see Figure 2–39), and one mol- ecule of the ribonucleoside triphosphate GTP from GDP

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Flashcard 1483153476876

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#biochem #biology #cell
Question
n total, the complete oxidation of a molecule of glucose to H 2 O and CO 2 is used by the cell to produce about [...] molecules of ATP.
Answer
30

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n total, the complete oxidation of a molecule of glucose to H 2 O and CO 2 is used by the cell to produce about 30 molecules of ATP.

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Flashcard 1483155049740

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#biochem #biology #cell
Question
All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from [...]
Answer
glucose.

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pan>All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from glucose.<span><body><html>

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Flashcard 1483156622604

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#biochem #biology #cell
Question
All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino [...], whereas the ribose and deoxyribose sugars are derived from glucose.
Answer
acids glutamine, aspartic acid, and glycine

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All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from glucose.

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Flashcard 1483158195468

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#biochem #biology #cell
Question
All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the [...] are derived from glucose.
Answer
ribose and deoxyribose sugars

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All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from glucose.

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Flashcard 1483159768332

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#biochem #biology #cell
Question
All of the [...] (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from glucose.
Answer
nitrogens in the purine and pyrimidine bases

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All of the nitrogens in the purine and pyrimidine bases (as well as some of the carbons) are derived from the plentiful amino acids glutamine, aspartic acid, and glycine, whereas the ribose and deoxyribose sugars are derived from glucose.<

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Flashcard 1483161341196

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#biochem #biology #cell
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Sulfur is abundant on Earth in its most oxidized form, [...].
Answer
sulfate (SO 4 2– )

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Sulfur is abundant on Earth in its most oxidized form, sulfate (SO 4 2– ). To be useful for life, sulfate must be reduced to sulfide (S 2– ), the oxidation state of sulfur required for the synthesis of essential biological molecules, including the amino ac

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To be useful for life, sulfate must be reduced to sulfide (S 2– )
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Sulfur is abundant on Earth in its most oxidized form, sulfate (SO 4 2– ). To be useful for life, sulfate must be reduced to sulfide (S 2– ), the oxidation state of sulfur required for the synthesis of essential biological molecules, including the amino acids methionine and cysteine, coenzyme A (see Figure 2–39), and the i

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Flashcard 1483164486924

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#biochem #biology #cell
Question
Sulfur is abundant on Earth in its most oxidized form, sulfate (SO 4 2– ). To be useful for life, sulfate must be reduced to sulfide (S 2– ), the oxidation state of sulfur required for the synthesis of essential biological molecules, including the [...] (see Figure 14–16)
Answer
amino acids methionine and cysteine, coenzyme A (see Figure 2–39), and the iron-sulfur centers essential for electron transport

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is abundant on Earth in its most oxidized form, sulfate (SO 4 2– ). To be useful for life, sulfate must be reduced to sulfide (S 2– ), the oxidation state of sulfur required for the synthesis of essential biological molecules, including the <span>amino acids methionine and cysteine, coenzyme A (see Figure 2–39), and the iron-sulfur centers essential for electron transport (see Figure 14–16)<span><body><html>

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Flashcard 1483169205516

Question
[default - edit me]
Answer
The pressure in the pipe is nearest (A) 843 Pa (B) 981 Pa (C) 1270 P

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Flashcard 1483508419852

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#biochem #biology #cell
Question
Humans and other animals cannot [...] and must therefore acquire the sulfur they need for their metabolism in the food that they eat
Answer
reduce sulfate

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Humans and other animals cannot reduce sulfate and must therefore acquire the sulfur they need for their metabolism in the food that they eat

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Flashcard 1483512089868

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#biochem #biology #cell
Question
Humans and other animals cannot reduce sulfate and must therefore [...]
Answer
acquire the sulfur they need for their metabolism in the food that they eat

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Humans and other animals cannot reduce sulfate and must therefore acquire the sulfur they need for their metabolism in the food that they eat

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Flashcard 1483558751500

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#biochem #biology #cell
Question
The characteristic “size” for each atom is specified by [...]. The contact distance between any two noncovalently bonded atoms is the sum of their van der Waals radii
Answer
a unique van der Waals radius

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The characteristic “size” for each atom is specified by a unique van der Waals radius. The contact distance between any two noncovalently bonded atoms is the sum of their van der Waals radii

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Flashcard 1483563470092

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#biochem #biology #cell
Question
The characteristic “size” for each atom is specified by a unique van der Waals radius. The contact distance between any two noncovalently bonded atoms is the [...]
Answer
sum of their van der Waals radii

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The characteristic “size” for each atom is specified by a unique van der Waals radius. The contact distance between any two noncovalently bonded atoms is the sum of their van der Waals radii

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Flashcard 1483568188684

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#biochem #biology #cell
Question
The characteristic “size” for each atom is specified by a unique van der Waals radius. The [...] is the sum of their van der Waals radii
Answer
contact distance between any two noncovalently bonded atoms

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The characteristic “size” for each atom is specified by a unique van der Waals radius. The contact distance between any two noncovalently bonded atoms is the sum of their van der Waals radii

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Flashcard 1483658890508

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#matlab #programming
Question
[...] can also be done with the reshape function
Answer
Reshaping

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Reshaping can also be done with the reshape function

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Flashcard 1483663609100

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Question
Reshaping can also be done with the [...] function
Answer
reshape

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Reshaping can also be done with the reshape function

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Flashcard 1483673570572

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#matlab #programming
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On the right-hand side of an assignment, [...] gives all the elements of a strung out by columns in one long column vector
Answer
a(:)

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On the right-hand side of an assignment, a(:) gives all the elements of a strung out by columns in one long column vector

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Flashcard 1483679337740

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#matlab #programming
Question
On the right-hand side of an assignment, a(:) gives [...]
Answer
all the elements of a strung out by columns in one long column vector

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On the right-hand side of an assignment, a(:) gives all the elements of a strung out by columns in one long column vector

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Flashcard 1483693493516

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#matlab #programming
Question
As a special case, [...] may be used to replace all the elements of a matrix with a scalar, e.g., a(:) = -1
Answer
a single colon subscript

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As a special case, a single colon subscript may be used to replace all the elements of a matrix with a scalar, e.g., a(:) = -1

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Flashcard 1483699260684

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#matlab #programming
Question
As a special case, a single colon subscript may be used to [...], e.g., a(:) = -1
Answer
replace all the elements of a matrix with a scalar

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As a special case, a single colon subscript may be used to replace all the elements of a matrix with a scalar, e.g., a(:) = -1

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Flashcard 1483706076428

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#matlab #programming
Question
You can’t delete a single element from a matrix while keeping it a matrix, so a statement like [...] results in an error
Answer
a(1,2) = [ ]

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You can’t delete a single element from a matrix while keeping it a matrix, so a statement like a(1,2) = [ ] results in an error

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Flashcard 1483723377932

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#deeplearning #neuralnetworks
Question
T o analyze ho w man y solutions the equation has, we can think of the columns of A as sp ecifying [...] (the p oin t sp ecified b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x sp ecifies ho w far we should trav el in eac h of these directions, with x i sp ecifying how far to mo v e in the direction of column :
Answer
different directions we can tra v el from the origin

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T o analyze ho w man y solutions the equation has, we can think of the columns of A as sp ecifying different directions we can tra v el from the origin (the p oin t sp ecified b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x sp ecifies ho w far we should trav el in ea

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Flashcard 1483731242252

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#deeplearning #neuralnetworks
Question
T o analyze ho w man y solutions the equation has, we can think of the columns of A as sp ecifying different directions we can tra v el from the origin (the p oin t sp ecified b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x [...], with x i sp ecifying how far to mo v e in the direction of column i:
Answer
sp ecifies ho w far we should trav el in eac h of these directions

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we can think of the columns of A as sp ecifying different directions we can tra v el from the origin (the p oin t sp ecified b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x <span>sp ecifies ho w far we should trav el in eac h of these directions, with x i sp ecifying how far to mo v e in the direction of column :<span><body><html>

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Flashcard 1483737009420

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#deeplearning #neuralnetworks
Question
T o analyze ho w man y solutions the equation has, we can think of the columns of A as sp ecifying different directions we can tra v el from the origin (the p oin t sp ecified b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x sp ecifies ho w far we should trav el in eac h of these directions, with x i [...]n :
Answer
sp ecifying how far to mo v e in the direction of colum

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ra v el from the origin (the p oin t sp ecified b y the v ector of all zeros), and determine ho w many wa ys there are of reac hing b . In this view, each element of x sp ecifies ho w far we should trav el in eac h of these directions, with x i <span>sp ecifying how far to mo v e in the direction of column :<span><body><html>

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Flashcard 1483786292492

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#bayes #programming #r #statistics
Question
The “evidence” for the model, p(D), is [...]
Answer
the overall probability of the data according to the model, determined by averaging across all possible parameter values weighted by the strength of belief in those parameter value

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The “evidence” for the model, p(D), is the overall probability of the data according to the model, determined by averaging across all possible parameter values weighted by the strength of belief in those parameter value

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Flashcard 1483789962508

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#bayes #programming #r #statistics
Question
The [...] for the model, p(D), is the overall probability of the data according to the model, determined by averaging across all possible parameter values weighted by the strength of belief in those parameter value
Answer
“evidence”

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The “evidence” for the model, p(D), is the overall probability of the data according to the model, determined by averaging across all possible parameter values weighted by the strength of belief in th

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Flashcard 1483800972556

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#bayes #programming #r #statistics
Question
In many models, the probability of data, p(D|θ), does not depend in any way on other data. That is, the joint probability p(D, D |θ) equals p(D|θ)·p(D |θ). In other words, in this sort of model, the data probabilities are [...]. Under this condition, then the order of updating has no effect of the final posterior
Answer
independent (recall that independence was defined in Section 4.4.2)

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body>In many models, the probability of data, p(D|θ), does not depend in any way on other data. That is, the joint probability p(D, D |θ) equals p(D|θ)·p(D |θ). In other words, in this sort of model, the data probabilities are independent (recall that independence was defined in Section 4.4.2). Under this condition, then the order of updating has no effect of the final posterior<body><html>

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Flashcard 1483813031180

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#bayes #programming #r #statistics
Question
a general phenomenon in Bayesian inference: The posterior is a compromise [...].
Answer
between the prior distribution and the likelihood function

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a general phenomenon in Bayesian inference: The posterior is a compromise between the prior distribution and the likelihood function.

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Flashcard 1483824041228

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#bayes #programming #r #statistics
Question
The compromise favors the prior to the extent that [...]. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distribution is flat and the data are many.
Answer
the prior distribution is sharply peaked and the data are few

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The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distribution is flat and the data are many.

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Flashcard 1483828759820

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#bayes #programming #r #statistics
Question
The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that [...]
Answer
the prior distribution is flat and the data are many.

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The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distribution is flat and the data are many.

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Flashcard 1483834526988

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#bayes #programming #r #statistics
Question
The compromise favors the [...] to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distribution is flat and the data are many.
Answer
prior

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The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distributio

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Flashcard 1483838197004

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#bayes #programming #r #statistics
Question
The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the [...] to the extent that the prior distribution is flat and the data are many.
Answer
likelihood function (i.e., the data)

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The compromise favors the prior to the extent that the prior distribution is sharply peaked and the data are few. The compromise favors the likelihood function (i.e., the data) to the extent that the prior distribution is flat and the data are many.

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Flashcard 1483850255628

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#bayes #programming #r #statistics
Question
the mode of the posterior distribution is between [...], but the posterior mode is closer to the likelihood mode for larger sample sizes
Answer
the mode of the prior distribution and the mode of the likelihood function

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the mode of the posterior distribution is between the mode of the prior distribution and the mode of the likelihood function, but the posterior mode is closer to the likelihood mode for larger sample sizes

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Flashcard 1483858119948

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#bayes #programming #r #statistics
Question
the mode of the posterior distribution is between the mode of the prior distribution and the mode of the likelihood function, but the posterior mode is closer to [...] for larger sample sizes
Answer
the likelihood mode

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the mode of the posterior distribution is between the mode of the prior distribution and the mode of the likelihood function, but the posterior mode is closer to the likelihood mode for larger sample sizes

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Flashcard 1483870178572

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#matlab #programming
Question
the functions [...] generate matrices of 1s, 0s and random numbers, respectively. With a single argument n, they generate n × n (square) matrices. With two arguments n and m they generate n × m ma- trices.
Answer
zeros, ones and rand

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the functions zeros, ones and rand generate matrices of 1s, 0s and random numbers, respectively. With a single argument n, they generate n × n (square) matrices. With two arguments n and m they generate n × m ma- trices.

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Flashcard 1483875945740

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#matlab #programming
Question
The function [...] generates an n × n identity matrix, i.e., a matrix with 1s on the main ‘diagonal’, and 0s everywhere else
Answer
eye(n)

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The function eye(n) generates an n × n identity matrix, i.e., a matrix with 1s on the main ‘diagonal’, and 0s everywhere else

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Flashcard 1483882761484

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#matlab #programming
Question
[...] extracts or creates a diagonal
Answer
diag

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diag extracts or creates a diagonal

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Flashcard 1483886431500

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Question
diag [...]
Answer
extracts or creates a diagonal

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diag extracts or creates a diagonal

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Flashcard 1483891150092

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Question
[...] extracts the upper triangular part
Answer
triu

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triu extracts the upper triangular part

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Flashcard 1483895868684

Tags
#matlab #programming
Question
triu [...]
Answer
extracts the upper triangular part

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triu extracts the upper triangular part

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Flashcard 1483907927308

Tags
#biochem #biology #cell
Question
although the overall conformation of each pro- tein is unique, two regular folding patterns are often found within them. Both pat- terns were discovered more than [...] ago from studies of hair and silk
Answer
60 years

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although the overall conformation of each pro- tein is unique, two regular folding patterns are often found within them. Both pat- terns were discovered more than 60 years ago from studies of hair and silk

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Flashcard 1483910548748

Tags
#biochem #biology #cell
Question
although the overall conformation of each pro- tein is unique, two regular folding patterns are often found within them. Both pat- terns were discovered more than 60 years ago from studies of [...]
Answer
hair and silk

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although the overall conformation of each pro- tein is unique, two regular folding patterns are often found within them. Both pat- terns were discovered more than 60 years ago from studies of hair and silk

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Flashcard 1483919461644

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#biochem #biology #cell
Question
Within [...] of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids
Answer
a year

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Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly comm

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Flashcard 1483924180236

Tags
#biochem #biology #cell
Question
Within a year of the discovery of the α helix, a second folded structure, called a [...], was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids
Answer
β sheet

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Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups

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Flashcard 1483926801676

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#biochem #biology #cell
Question
Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein [...], the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids
Answer
fibroin

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Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, with

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Flashcard 1483931520268

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#biochem #biology #cell
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Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of [...]. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids
Answer
silk

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Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains o

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Flashcard 1483938336012

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Question
Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because [...]
Answer
they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids

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l>Within a year of the discovery of the α helix, a second folded structure, called a β sheet, was found in the protein fibroin, the major constituent of silk. These two patterns are particularly common because they result from hydro- gen-bonding between the N–H and C=O groups in the polypeptide backbone, without involving the side chains of the amino acids<html>

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Flashcard 1483944103180

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#matlab #programming
Question
[...] inverse.
Answer
inv

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inv inverse.

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Flashcard 1483947773196

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Question
inv [...]
Answer
inverse.

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inv inverse.

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Flashcard 1483955637516

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#matlab #programming
Question
[...] orthogonal factorization
Answer
qr

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qr orthogonal factorization

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Flashcard 1483957210380

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#matlab #programming
Question
qr [...]
Answer
orthogonal factorization

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qr orthogonal factorization

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Flashcard 1483970317580

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To see how MATLAB solves this system, first recall that the left division operator \ may be used on scalars, i.e., a\bis the same as b/aif a and b are scalars. However, it can also be used on vectors and matrices, in order to [...]
Answer
solve linear equations

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body>To see how MATLAB solves this system, first recall that the left division operator \ may be used on scalars, i.e., a\bis the same as b/aif a and b are scalars. However, it can also be used on vectors and matrices, in order to solve linear equations<body><html>

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Flashcard 1483976084748

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When we have more equations than unknowns, the system is called [...]
Answer
over- determined

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When we have more equations than unknowns, the system is called over- determined

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Flashcard 1483982900492

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Question
When we [...], the system is called over- determined
Answer
have more equations than unknowns

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When we have more equations than unknowns, the system is called over- determined

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Flashcard 1484063116556

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The residual r=A*x-b is now r= -0.3333 -0.3333 0.3333 What happens in this case is that MATLAB produces the [...]. This is the value of x which makes the magnitude of r, i.e., r(1) 2 + r(2) 2 + r(3)2 , as small as possible.
Answer
least squares best fit

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The residual r=A*x-b is now r= -0.3333 -0.3333 0.3333 What happens in this case is that MATLAB produces the least squares best fit. This is the value of x which makes the magnitude of r, i.e., r(1) 2 + r(2) 2 + r(3) 2 , as small as possible.

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Flashcard 1484073078028

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The residual r=A*x-b is now r= -0.3333 -0.3333 0.3333 What happens in this case is that MATLAB produces the least squares best fit. This is the value of x which [...]
Answer
makes the magnitude of r, i.e., r(1) 2 + r(2) 2 + r(3)2 , as small as possible.

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The residual r=A*x-b is now r= -0.3333 -0.3333 0.3333 What happens in this case is that MATLAB produces the least squares best fit. This is the value of x which makes the magnitude of r, i.e., r(1) 2 + r(2) 2 + r(3) 2 , as small as possible.

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Flashcard 1484080942348

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If there are fewer equations than unknowns, the system is called [...]. In this case there are an infinite number of solutions; MATLAB will find one which has zeros for some of the unknowns.
Answer
under- determined

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If there are fewer equations than unknowns, the system is called under- determined. In this case there are an infinite number of solutions; MATLAB will find one which has zeros for some of the unknowns.

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Flashcard 1484086709516

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If there are fewer equations than unknowns, the system is called under- determined. In this case there are an [...] number of solutions; MATLAB will find one which has zeros for some of the unknowns.
Answer
infinite

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If there are fewer equations than unknowns, the system is called under- determined. In this case there are an infinite number of solutions; MATLAB will find one which has zeros for some of the unknowns.

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Flashcard 1484092476684

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Question
If there are fewer equations than unknowns, the system is called under- determined. In this case there are an infinite number of solutions; MATLAB will [...]
Answer
find one which has zeros for some of the unknowns.

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If there are fewer equations than unknowns, the system is called under- determined. In this case there are an infinite number of solutions; MATLAB will find one which has zeros for some of the unknowns.

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Flashcard 1484100341004

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A system like this is called [...] meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning
Answer
ill-conditioned,

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A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning</s

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Flashcard 1484106108172

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A system like this is called ill-conditioned, meaning that a [...]. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning
Answer
small change in the co- efficients leads to a large change in the solution

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A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning

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Flashcard 1484108729612

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A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function [...] returns the condition estimator, which tests for ill conditioning
Answer
rcond

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A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning

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Flashcard 1484113448204

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Question
A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the [...]
Answer
condition estimator, which tests for ill conditioning

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A system like this is called ill-conditioned, meaning that a small change in the co- efficients leads to a large change in the solution. The MATLAB function rcond returns the condition estimator, which tests for ill conditioning

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Flashcard 1484119215372

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Question
The function [...] provides a neat visualization of sparse matrices.
Answer
spy

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The function spy provides a neat visualization of sparse matrices.

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Flashcard 1484121836812

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Question
The function spy provides a [...]
Answer
neat visualization of sparse matrices.

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The function spy provides a neat visualization of sparse matrices.

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Flashcard 1484131798284

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#bayes #programming #r #statistics
Question
The space of possibilities is the j[...]. If we represent each parameter with a comb of, say, 1,000 values, then for P parameters there are 1,000 P combinations of parameter values.
Answer
oint parameter space involving all combinations of parameter values

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The space of possibilities is the joint parameter space involving all combinations of parameter values. If we represent each parameter with a comb of, say, 1,000 values, then for P parameters there are 1,000 P combinations of parameter values.

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Flashcard 1484147789068

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#bayes #programming #r #statistics
Question
The space of possibilities is the joint parameter space involving all combinations of parameter values. If we represent each parameter with a comb of, say, 1,000 values, then for P parameters there are [...] of parameter values.
Answer
1,000 P combinations

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The space of possibilities is the joint parameter space involving all combinations of parameter values. If we represent each parameter with a comb of, say, 1,000 values, then for P parameters there are 1,000 P combinations of parameter values.

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Flashcard 1484166139148

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Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a [...] to the helix, with the C-terminus having a partial negative and the N-terminus a partial positive charge (
Answer
polarity

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Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a polarity to the helix, with the C-terminus having a partial negative and the N-terminus a partial positive charge (

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Flashcard 1484168760588

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Question
Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a polarity to the helix, with the C-terminus having a [...] and the N-terminus a partial positive charge (
Answer
partial negative

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Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a polarity to the helix, with the C-terminus having a partial negative and the N-terminus a partial positive charge (

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Flashcard 1484173479180

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Question
Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a polarity to the helix, with the C-terminus having a partial negative and the N-terminus a [...] charge (
Answer
partial positive

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y>Note that all of the N–H groups point up in this diagram and that all of the C=O groups point down (toward the C-terminus); this gives a polarity to the helix, with the C-terminus having a partial negative and the N-terminus a partial positive charge (<body><html>

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Flashcard 1484186586380

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The β sheet is shown in (C) and (D). In this example, adjacent peptide chains run in [...] directions. Hydrogen-bonding between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each strand alternately project above and below the plane of the sheet
Answer
opposite (antiparallel)

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The β sheet is shown in (C) and (D). In this example, adjacent peptide chains run in opposite (antiparallel) directions. Hydrogen-bonding between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each

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Flashcard 1484193402124

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Question
The β sheet is shown in (C) and (D). In this example, adjacent peptide chains run in opposite (antiparallel) directions. Hydrogen-bonding between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each strand [...]
Answer
alternately project above and below the plane of the sheet

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nt peptide chains run in opposite (antiparallel) directions. Hydrogen-bonding between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each strand <span>alternately project above and below the plane of the sheet<span><body><html>

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Flashcard 1484194974988

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The β sheet is shown in (C) and (D). In this example, adjacent peptide chains run in opposite (antiparallel) directions. [...] between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each strand alternately project above and below the plane of the sheet
Answer
Hydrogen-bonding

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The β sheet is shown in (C) and (D). In this example, adjacent peptide chains run in opposite (antiparallel) directions. Hydrogen-bonding between peptide bonds in different strands holds the individual polypeptide chains (strands) together in a β sheet, and the amino acid side chains in each strand alternately project a

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Flashcard 1484196547852

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An [...] is generated when a single polypeptide chain twists around on itself to form a rigid cylinder. A hydrogen bond forms between every fourth peptide bond, linking the C=O of one peptide bond to the N–H of another (see Figure 3–7A). This gives rise to a regular helix with a complete turn every 3.6 amino acids.
Answer
α helix

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An α helix is generated when a single polypeptide chain twists around on itself to form a rigid cylinder. A hydrogen bond forms between every fourth peptide bond, linking the C=O of one peptide

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Flashcard 1484198120716

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Question
An α helix is generated when a single polypeptide chain twists around on itself to form a rigid cylinder. A hydrogen bond forms between every [...] peptide bond, linking the C=O of one peptide bond to the N–H of another (see Figure 3–7A). This gives rise to a regular helix with a complete turn every 3.6 amino acids.
Answer
fourth

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An α helix is generated when a single polypeptide chain twists around on itself to form a rigid cylinder. A hydrogen bond forms between every fourth peptide bond, linking the C=O of one peptide bond to the N–H of another (see Figure 3–7A). This gives rise to a regular helix with a complete turn every 3.6 amino acids.

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Flashcard 1484199693580

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Question
An α helix is generated when a single polypeptide chain twists around on itself to form a rigid cylinder. A hydrogen bond forms between every fourth peptide bond, linking the C=O of one peptide bond to the N–H of another (see Figure 3–7A). This gives rise to a regular helix with a complete turn every [...] amino acids.
Answer
3.6

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around on itself to form a rigid cylinder. A hydrogen bond forms between every fourth peptide bond, linking the C=O of one peptide bond to the N–H of another (see Figure 3–7A). This gives rise to a regular helix with a complete turn every <span>3.6 amino acids.<span><body><html>

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Flashcard 1484201266444

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Question
α helices wrap around each other to form a particularly sta- ble structure, known as a [...] This structure can form when the two (or in some cases, three or four) α helices have most of their nonpolar (hydrophobic) side chains on one side, so that they can twist around each other with these side chains facing inward
Answer
coiled-coil.

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α helices wrap around each other to form a particularly sta- ble structure, known as a coiled-coil. This structure can form when the two (or in some cases, three or four) α helices have most of their nonpolar (hydrophobic) side chains on one side, so that they can twist around each

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Flashcard 1484202839308

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Question
[...] wrap around each other to form a particularly sta- ble structure, known as a coiled-coil. This structure can form when the two (or in some cases, three or four) α helices have most of their nonpolar (hydrophobic) side chains on one side, so that they can twist around each other with these side chains facing inward
Answer
α helices

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α helices wrap around each other to form a particularly sta- ble structure, known as a coiled-coil. This structure can form when the two (or in some cases, three or four) α helices have most of

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Flashcard 1484204412172

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Question
α helices wrap around each other to form a particularly sta- ble structure, known as a coiled-coil. This structure can form when [...]
Answer
the two (or in some cases, three or four) α helices have most of their nonpolar (hydrophobic) side chains on one side, so that they can twist around each other with these side chains facing inward

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α helices wrap around each other to form a particularly sta- ble structure, known as a coiled-coil. This structure can form when the two (or in some cases, three or four) α helices have most of their nonpolar (hydrophobic) side chains on one side, so that they can twist around each other with these side chains facing inward

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Flashcard 1484205985036

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Question
This is the protein domain, [...]
Answer
a substructure produced by any contiguous part of a polypeptide chain that can fold independently of the rest of the protein into a compact, stable structure.

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This is the protein domain, a substructure produced by any contiguous part of a polypeptide chain that can fold independently of the rest of the protein into a compact, stable structure.

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Flashcard 1484207557900

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Question
This is the [...], a substructure produced by any contiguous part of a polypeptide chain that can fold independently of the rest of the protein into a compact, stable structure.
Answer
protein domain

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This is the protein domain, a substructure produced by any contiguous part of a polypeptide chain that can fold independently of the rest of the protein into a compact, stable structure. </

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Flashcard 1484209130764

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Question
A domain usually contains between [...] amino acids, and it is the modular unit from which many larger proteins are constructed
Answer
40 and 350

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A domain usually contains between 40 and 350 amino acids, and it is the modular unit from which many larger proteins are constructed

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Flashcard 1484210703628

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Question
the [...], which functions in signaling pathways inside vertebrate cells
Answer
Src protein kinase

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the Src protein kinase, which functions in signaling pathways inside vertebrate cells

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Flashcard 1484212276492

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Question
the Src protein kinase, which functions in [...] inside vertebrate cells
Answer
signaling pathways

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the Src protein kinase, which functions in signaling pathways inside vertebrate cells

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Flashcard 1484213849356

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Question
The smallest protein molecules contain only [...] domain, whereas larger proteins can contain several dozen domains, often connected to each other by short, relatively unstructured lengths of polypeptide chain that can act as flexible hinges between domains.
Answer
a single

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The smallest protein molecules contain only a single domain, whereas larger proteins can contain several dozen domains, often connected to each other by short, relatively unstructured lengths of polypeptide chain that can act as flexibl

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Flashcard 1484215422220

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Question
The smallest protein molecules contain only a single domain, whereas larger proteins can contain [...] domains, often connected to each other by short, relatively unstructured lengths of polypeptide chain that can act as flexible hinges between domains.
Answer
several dozen

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The smallest protein molecules contain only a single domain, whereas larger proteins can contain several dozen domains, often connected to each other by short, relatively unstructured lengths of polypeptide chain that can act as flexible hinges between domains.

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Flashcard 1484216995084

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Question
The smallest protein molecules contain only a single domain, whereas larger proteins can contain several dozen domains, often connected to each other by [...]
Answer
short, relatively unstructured lengths of polypeptide chain that can act as flexible hinges between domains.

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The smallest protein molecules contain only a single domain, whereas larger proteins can contain several dozen domains, often connected to each other by short, relatively unstructured lengths of polypeptide chain that can act as flexible hinges between domains.

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Flashcard 1484218567948

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Question
Since each of the 20 amino acids is chemically distinct and each can, in princi- ple, occur at any position in a protein chain, there are [...] different possible polypeptide chains four amino acids long, or 20 n different pos- sible polypeptide chains n amino acids long. For a typical protein length of about 300 amino acids, a cell could theoretically make more than 10 390 (20 300 ) different polypeptide chains
Answer
20 × 20 × 20 × 20 = 160,000

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Since each of the 20 amino acids is chemically distinct and each can, in princi- ple, occur at any position in a protein chain, there are 20 × 20 × 20 × 20 = 160,000 different possible polypeptide chains four amino acids long, or 20 n different pos- sible polypeptide chains n amino acids long. For a typical protein length of about 300 amino acids

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Flashcard 1484220140812

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Question
Since each of the 20 amino acids is chemically distinct and each can, in princi- ple, occur at any position in a protein chain, there are 20 × 20 × 20 × 20 = 160,000 different possible polypeptide chains four amino acids long, or 20 n different pos- sible polypeptide chains n amino acids long. For a typical protein length of about 300 amino acids, a cell could theoretically make more than [...] different polypeptide chains
Answer
10 390 (20 300 )

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20 = 160,000 different possible polypeptide chains four amino acids long, or 20 n different pos- sible polypeptide chains n amino acids long. For a typical protein length of about 300 amino acids, a cell could theoretically make more than <span>10 390 (20 300 ) different polypeptide chains<span><body><html>

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Flashcard 1484221713676

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Question
Many similar examples show that two pro- teins with more than [...] identity in their amino acid sequences usually share the same overall structure
Answer
25%

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Many similar examples show that two pro- teins with more than 25% identity in their amino acid sequences usually share the same overall structure

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Flashcard 1484223286540

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Question
Many similar examples show that two pro- teins with more than 25% identity in their amino acid sequences usually [...]
Answer
share the same overall structure

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Many similar examples show that two pro- teins with more than 25% identity in their amino acid sequences usually share the same overall structure

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Flashcard 1484224859404

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Question
there are a limited number of ways in which protein domains fold up in nature—maybe as few as [...], if we consider all organisms. For most of these so-called protein folds, representative structures have been determined.
Answer
2000

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there are a limited number of ways in which protein domains fold up in nature—maybe as few as 2000, if we consider all organisms. For most of these so-called protein folds, representative structures have been determined.

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Flashcard 1484226432268

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Question
The present database of known protein sequences contains more than [...] entries
Answer
twenty million

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The present database of known protein sequences contains more than twenty million entries

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Flashcard 1484228005132

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Question
The encoded polypeptides range widely in size, from [...] amino acids to a gigantic pro- tein of 33,000 amino acids.
Answer
6

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The encoded polypeptides range widely in size, from 6 amino acids to a gigantic pro- tein of 33,000 amino acids.

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Flashcard 1484229577996

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Question
The encoded polypeptides range widely in size, from 6 amino acids to a gigantic pro- tein of [...] amino acids.
Answer
33,000

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The encoded polypeptides range widely in size, from 6 amino acids to a gigantic pro- tein of 33,000 amino acids.

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Flashcard 1484231150860

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Question
most proteins are composed of a series of protein domains, in which different regions of the polypeptide chain fold independently to form compact structures. Such multidomain proteins are believed to have originated from the [process] , cre- ating a new gene.
Answer
accidental joining of the DNA sequences that encode each domain

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dy>most proteins are composed of a series of protein domains, in which different regions of the polypeptide chain fold independently to form compact structures. Such multidomain proteins are believed to have originated from the accidental joining of the DNA sequences that encode each domain, cre- ating a new gene.<body><html>

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Flashcard 1484232723724

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In an evolutionary process called [...], many large proteins have evolved through the joining of preexisting domains in new com- binations (Figure 3–14). Novel binding surfaces have often been created at the juxtaposition of domains, and many of the functional sites where proteins bind to small molecules are found to be located there.
Answer
domain shuffling

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In an evolutionary process called domain shuffling, many large proteins have evolved through the joining of preexisting domains in new com- binations (Figure 3–14). Novel binding surfaces have often been created at the juxtaposition o

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Flashcard 1484234296588

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Question
β-sheet-based domains may have achieved their evolutionary success because [...]
Answer
they provide a convenient framework for the generation of new binding sites for ligands, requiring only small changes to their protruding loops

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β-sheet-based domains may have achieved their evolutionary success because they provide a convenient framework for the generation of new binding sites for ligands, requiring only small changes to their protruding loops

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Flashcard 1484235869452

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Question
Stiff extended structures composed of a series of domains are especially common in [...] and in the extracellular portions of cell-surface receptor proteins.
Answer
extracellular matrix molecules

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Stiff extended structures composed of a series of domains are especially common in extracellular matrix molecules and in the extracellular portions of cell-surface receptor proteins.

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Flashcard 1484237442316

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Question
Stiff extended structures composed of a series of domains are especially common in extracellular matrix molecules and in the [...]
Answer
extracellular portions of cell-surface receptor proteins.

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Stiff extended structures composed of a series of domains are especially common in extracellular matrix molecules and in the extracellular portions of cell-surface receptor proteins.

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Flashcard 1484239015180

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Question
[...] composed of a series of domains are especially common in extracellular matrix molecules and in the extracellular portions of cell-surface receptor proteins.
Answer
Stiff extended structures

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Stiff extended structures composed of a series of domains are especially common in extracellular matrix molecules and in the extracellular portions of cell-surface receptor proteins.

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Flashcard 1484241636620

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Question
N- and C-terminal ends at opposite poles of the domain. When the DNA encoding such a domain undergoes [...], which is not unusual in the evolution of genomes (discussed in Chapter 4), the duplicated domains with this “in-line” arrangement can be readily linked in series to form extended structures—either with themselves or with other in-line domains
Answer
tandem duplica- tion

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N- and C-terminal ends at opposite poles of the domain. When the DNA encoding such a domain undergoes tandem duplica- tion, which is not unusual in the evolution of genomes (discussed in Chapter 4), the duplicated domains with this “in-line” arrangement can be readily linked in series to form extended str

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Flashcard 1484243209484

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Question
[...] of all domain families are common to archaea, bacteria, and eukaryotes, only about 5% of the two-domain combi- nations are similarly shared.
Answer
half

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half of all domain families are common to archaea, bacteria, and eukaryotes, only about 5% of the two-domain combi- nations are similarly shared.

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Flashcard 1484244782348

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Question
half of all domain families are common to archaea, bacteria, and eukaryotes, only about [...] of the two-domain combi- nations are similarly shared.
Answer
5%

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half of all domain families are common to archaea, bacteria, and eukaryotes, only about 5% of the two-domain combi- nations are similarly shared.

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Flashcard 1484246355212

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Question
most proteins containing especially useful two-domain combinations arose through [...] rel- atively late in evolution
Answer
domain shuffling

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most proteins containing especially useful two-domain combinations arose through domain shuffling rel- atively late in evolution

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Flashcard 1484247928076

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Question
most proteins containing especially useful two-domain combinations arose through domain shuffling rel- atively [...] in evolution
Answer
late

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most proteins containing especially useful two-domain combinations arose through domain shuffling rel- atively late in evolution

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Flashcard 1484249500940

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Question
we currently lack even the tiniest hint of what the function might be for more than [...] of the proteins that have thus far been identified through examining the human genome
Answer
10,000

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we currently lack even the tiniest hint of what the function might be for more than 10,000 of the proteins that have thus far been identified through examining the human genome

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Flashcard 1484251073804

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Question
combinations of protein domains, with the result that there are nearly [...] as many combinations of domains found in human proteins as in a worm or a fly.
Answer
twice

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combinations of protein domains, with the result that there are nearly twice as many combinations of domains found in human proteins as in a worm or a fly.

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Flashcard 1484252646668

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Question
Determining whether Ax = b has a solution th us amounts to testing whether [...] . This particular span is known as the column space range or the of . A
Answer
b is in the span of the columns of A

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Determining whether Ax = b has a solution th us amounts to testing whether b is in the span of the columns of A . This particular span is known as the column space range or the of . A

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Flashcard 1484255005964

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Question
Determining whether Ax = b has a solution th us amounts to testing whether b is in the span of the columns of A . This particular span is known as the [...]
Answer
column space range or the of . A

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Determining whether Ax = b has a solution th us amounts to testing whether b is in the span of the columns of A . This particular span is known as the column space range or the of . A

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Flashcard 1484257103116

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Question
Ha ving n m ≥ is only a necessary condition for ev ery p oin t to ha ve a solution. It is not a sufficien t condition, b ecause [...]
Answer
it is p ossible for some of the columns to b e redundan t.

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Ha ving n m ≥ is only a necessary condition for ev ery p oin t to ha ve a solution. It is not a sufficien t condition, b ecause it is p ossible for some of the columns to b e redundan t.

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Flashcard 1484258675980

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Question
Ha ving [...] is only a necessary condition for ev ery p oin t to ha ve a solution. It is not a sufficien t condition, b ecause it is p ossible for some of the columns to b e redundan t.
Answer
n m ≥

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Ha ving n m ≥ is only a necessary condition for ev ery p oin t to ha ve a solution. It is not a sufficien t condition, b ecause it is p ossible for some of the columns to b e redundan t.<

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Flashcard 1484260248844

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Question
Ha ving n m ≥ is only a necessary condition for [...] It is not a sufficien t condition, b ecause it is p ossible for some of the columns to b e redundan t.
Answer
ev ery p oin t to ha ve a solution.

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Ha ving n m ≥ is only a necessary condition for ev ery p oin t to ha ve a solution. It is not a sufficien t condition, b ecause it is p ossible for some of the columns to b e redundan t.

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Flashcard 1484261821708

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Question
F ormally , this kind of redundancy is kno wn as [...] . A set of v ectors is linearly indep enden t if no v ector in the set is a linear combination of the other vectors.
Answer
linear dep endence

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F ormally , this kind of redundancy is kno wn as linear dep endence . A set of v ectors is linearly indep enden t if no v ector in the set is a linear combination of the other vectors.

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Flashcard 1484263394572

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Question
F ormally , this kind of redundancy is kno wn as linear dep endence . A set of v ectors is linearly indep enden t if [...]
Answer
no v ector in the set is a linear combination of the other vectors.

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F ormally , this kind of redundancy is kno wn as linear dep endence . A set of v ectors is linearly indep enden t if no v ector in the set is a linear combination of the other vectors.

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Flashcard 1484264967436

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Question
the deriv ativ es of the [...] with resp ect to each element of x eac h dep end only on the corresp onding elemen t of x , while all of the deriv ativ es of the L 2 norm dep end on the en tire vector
Answer
squared L 2 norm

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the deriv ativ es of the squared L 2 norm with resp ect to each element of x eac h dep end only on the corresp onding elemen t of x , while all of the deriv ativ es of the L 2 norm dep end on the en tire vector</b

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Flashcard 1484266540300

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Question
the deriv ativ es of the squared L 2 norm with resp ect to each element of x eac h dep end only on [...] , while all of the deriv ativ es of the L 2 norm dep end on the en tire vector
Answer
the corresp onding elemen t of x

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the deriv ativ es of the squared L 2 norm with resp ect to each element of x eac h dep end only on the corresp onding elemen t of x , while all of the deriv ativ es of the L 2 norm dep end on the en tire vector

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Flashcard 1484268113164

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Question
the deriv ativ es of the squared L 2 norm with resp ect to each element of x eac h dep end only on the corresp onding elemen t of x , while all of the deriv ativ es of the L 2 norm dep end on [...]
Answer
the en tire vector

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the deriv ativ es of the squared L 2 norm with resp ect to each element of x eac h dep end only on the corresp onding elemen t of x , while all of the deriv ativ es of the L 2 norm dep end on the en tire vector

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Flashcard 1484269686028

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Question
The [...] is commonly used in machine learning when the difference b etw een zero and nonzero elements is v ery imp ortan t.
Answer
L 1 norm

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The L 1 norm is commonly used in machine learning when the difference b etw een zero and nonzero elements is v ery imp ortan t. Every time an element of x mo v es a w a y from 0 b y , the L 1 norm

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Flashcard 1484271258892

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Question
The L 1 norm is commonly used in machine learning when [...] is v ery imp ortan t. Every time an element of x mo v es a w a y from 0 b y , the L 1 norm increases b y .
Answer
the difference b etw een zero and nonzero elements

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The L 1 norm is commonly used in machine learning when the difference b etw een zero and nonzero elements is v ery imp ortan t. Every time an element of x mo v es a w a y from 0 b y , the L 1 norm increases b y .

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Flashcard 1484273618188

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Question
Diagonal matrices are of interest in part b ecause [...]
Answer
multiplying by a diagonal matrix is very computationally efficien t.

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Diagonal matrices are of interest in part b ecause multiplying by a diagonal matrix is very computationally efficien t.

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Flashcard 1484275191052

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Question
[...] matrices are of interest in part b ecause multiplying by a diagonal matrix is very computationally efficien t.
Answer
Diagonal

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Diagonal matrices are of interest in part b ecause multiplying by a diagonal matrix is very computationally efficien t.

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Flashcard 1484278336780

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Question
T o compute [...] , we only need to scale each element xi b y vi . In other w ords, diag(v)x = \(x\cdot y\)
Answer
diag(v)x

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T o compute diag(v)x , we only need to scale each element x i b y v i . In other w ords, diag(v)x = x⋅yx⋅y

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Flashcard 1484279909644

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Question
T o compute diag(v)x , we only need to [...] . In other w ords, diag(v)x = \(x\cdot y\)
Answer
scale each element xi b y vi

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T o compute diag(v)x , we only need to scale each element x i b y v i . In other w ords, diag(v)x = x⋅yx⋅y

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Flashcard 1484289084684

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Question
There are the 3 "A" core expressions the are used to protect the attacment relationship, and lead to the 5 different survival styles, What are these 3 core expressions? (each start with the letter A)
Answer
Anger, Aggression, Authenticitcy

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Flashcard 1484290919692

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Question
  1. When core needs are not met by children of rel trauma, what 4 negative experiences (3 start w/D and 1 w/ i) that the adaptive stratagies are trying to help deal with.
  2. What are the key parts of self does NARM empahsize to help develp a healthy regulatroy system?
Answer
  1. Disconnection, Dysregulation, Disorganisation and Issolation.
  2. Organized, Coherent, and Functional

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Flashcard 1484292754700

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Question
What is the goal of the Pride Based Counter Indenfication?
Answer
Pride based counter identifications reflect how we would liek to see ourselves or others see us, the paroix is the more energy a person invest in these defensive the stronger the shame based id becomes.

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Flashcard 1484295113996

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Question
What are the 12 steps of the NARM healing cycle?
Answer
  1. INCREASING AWARENESS OF ADAPTIVE SURVIVAL SYTLES
  2. Inquiry into identiy
  3. Disidentification from shame and pride based identifications
  4. Self hatred self rejection and jugements diminished
  5. Reconnection with core needs and capacities
  6. Resoriaton of connection and aliveness
  7. INCREASING CAPCITY FOR SOMATIC AWARENESS
  8. Somatic Mindfulness
  9. Discharge of shoke states
  10. increasing regulation and presence
  11. Increasing contact with the body
  12. Greater capacity for self regulations
(Rinse and repeat)

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Flashcard 1484296949004

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Question
What is the difference between psychodynamic and esoteric approaches to ego?
What are the pros/cons to these different approaches?
Answer
Psychodynamic work to sokidify the sense of identify and strengthen the ego, where as esoteric orientations hold that egow is an illusion and separates us fro Being and keeps us from experiencing teh spaciousness, fulidity, and fullness of our essential nature.
Both perspectives are important, Esoteric approaches address the limitations of what they call Ego, but generally do not incorarate the clinical awareness of the importance of attachement adn developmental trauma in creation of the sense of self.

Brief answer: psychodynmic focus on Strengthen ego vs Esoteric focus on release ego. Psychodynamic supports impact on ego caused by rel trauma while esoteric supports learning how to better regulate and re-wire the adaptive stratagies developed by the truama.

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Flashcard 1484298784012

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Question
What is the paradox of change?
Answer
The more we try to change ourselves, the more we prevent change from ocurring, on the other hand, the more we allow ourselves to fully experience who we are, the greater the possibility of change.
Brief: More we resist the more we persist.

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Flashcard 1484300619020

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Question
Name a core NARM principle that defines emotional health.
Answer
The capacity for connection with self and others defines emotional health.

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Flashcard 1484301929740

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Question
Elaborate on the 5 adaptive styles in terms of Survial Adaptions (disclousre) and Stratagy Used to PRotect the Attachement Relationship.
Answer
Core NeedSurvival AdaptionStratagey USed to Protect The Attach Rel
ConnectionForeclousing Connection, Disconnect from body and social engagementChildren gife up their very sense of existence, discounnect and attempt to become invisible.
AttunemetForeclosing the awareness and expression of personal needsChidrent give up thier own need in order to focus on the needs of others, particularly the needs of the parents
TrustForclosing trust and healthy interdependenceChildren give up their quthenticity in order to be who the parents want them to be: best friend, sport star, confidante, etc.
AutonomyForeclosing authentic expression, responding with what they think is expected of themChildren give up direct expression of independence in oreder not to feel abandoned or crushed
Love-SexualityForeclosing love and heart connection, foreclosing sexuality, Forclosing integration of love and sexualityChildren try to avoid rejection by perfecting themselves, hoping that they can win love through looks or performance.

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Flashcard 1484304026892

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Question
What does each adaptive style develop around to help make sense of the broad spectrum of symptoms often seen in developmental trauam?
Answer
Connection: develops around teh need for the conact and the fear of connection
Attunement: Develops around the conflict between having personal needs and the rejection of them.
Trust: develops around both the desire for and the fear of setting limits and expressing independence.
Love-Sexuality: Develops around wanting to love and be loved and the fear of vulnrability. It also develops aroudn the splitting of love and sexuality.


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Flashcard 1484306386188

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Question
[...] matrices do not hav e inv erses but it is still p ossible to multiply by them cheaply
Answer
Non-square diagonal

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Non-square diagonal matrices do not hav e inv erses but it is still p ossible to multiply by them cheaply

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Flashcard 1484307959052

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Question
Non-square diagonal matrices do not hav e [...] but it is still p ossible to multiply by them cheaply
Answer
inv erses

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Non-square diagonal matrices do not hav e inv erses but it is still p ossible to multiply by them cheaply

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Flashcard 1484309531916

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Question
Non-square diagonal matrices do not hav e inv erses but it is still p ossible [...]
Answer
to multiply by them cheaply

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Non-square diagonal matrices do not hav e inv erses but it is still p ossible to multiply by them cheaply

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Flashcard 1484311891212

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Question
A [...] is a vector with unit norm ||x||2 = 1
Answer
unit vector

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A unit vector is a vector with unit norm ||x|| 2 = 1

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Flashcard 1484313464076

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Question
A unit vector is a vector with unit norm [...]
Answer
||x||2 = 1

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A unit vector is a vector with unit norm ||x|| 2 = 1

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Flashcard 1484315036940

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A vector x and a vector y are [...] to each other if xTy = 0 .
Answer
orthogonal

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A vector x and a vector y are orthogonal to each other if x y = 0 .

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Flashcard 1484317396236

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Question
A vector x and a vector y are orthogonal to each other if [...]
Answer
xTy = 0 .

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A vector x and a vector y are orthogonal to each other if x T y = 0 .

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Flashcard 1484318969100

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Question
In R n , at most [...] v ectors ma y b e mutually orthogonal with nonzero norm. If the v ectors are not only orthogonal but also ha ve unit norm, we call them orthonormal
Answer
n

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In R n , at most n v ectors ma y b e mutually orthogonal with nonzero norm. If the v ectors are not only orthogonal but also ha ve unit norm, we call them orthonormal

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Flashcard 1484320541964

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Question
In R n , at most n v ectors ma y b e mutually orthogonal with nonzero norm. If the v ectors are not only orthogonal but also ha ve unit norm, we call them [...]
Answer
orthonormal

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In R n , at most n v ectors ma y b e mutually orthogonal with nonzero norm. If the v ectors are not only orthogonal but also ha ve unit norm, we call them orthonormal

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Flashcard 1484322114828

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Question
An [...] of a square matrix A is a non-zero vector v suc h that m ulti- plication b y A alters only the scale of v : Av = vλ
Answer
eigen v ector

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