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#deeplearning #protein #proteomics #research
Question
Sander14 developed a DSSP algorithm to classify SS into 8 fine-grained states. In particular, DSSP assigns [...] types for helix, [...] types for strand, and [...] types for coil
3, 2, 3

Tags
#deeplearning #protein #proteomics #research
Question
Sander14 developed a DSSP algorithm to classify SS into 8 fine-grained states. In particular, DSSP assigns [...] types for helix, [...] types for strand, and [...] types for coil
?

Tags
#deeplearning #protein #proteomics #research
Question
Sander14 developed a DSSP algorithm to classify SS into 8 fine-grained states. In particular, DSSP assigns [...] types for helix, [...] types for strand, and [...] types for coil
3, 2, 3
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Sander 14 developed a DSSP algorithm to classify SS into 8 fine-grained states. In particular, DSSP assigns 3 types for helix (G for 3 10 helix, H for alpha-helix, and I for pi-helix), 2 types for strand (E for beta-strand and B for beta-bridge), and 3 types for coil (T for beta-turn, S for hi

#### Original toplevel document

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields : Scientific Reports
S) refers to the local conformation of the polypeptide backbone of proteins. There are two regular SS states: alpha-helix (H) and beta-strand (E), as suggested by Pauling 13 more than 60 years ago, and one irregular SS type: coil region (C). <span>Sander 14 developed a DSSP algorithm to classify SS into 8 fine-grained states. In particular, DSSP assigns 3 types for helix (G for 3 10 helix, H for alpha-helix, and I for pi-helix), 2 types for strand (E for beta-strand and B for beta-bridge), and 3 types for coil (T for beta-turn, S for high curvature loop, and L for irregular). Overall, protein secondary structure can be regarded as a bridge that links the primary sequence and tertiary structure and thus, is used by many structure and functional analysis tools

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