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Bioinformatics
Article . 2004 . Peer-reviewed
Data sources: Crossref
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Bioinformatics
Article
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https://dx.doi.org/10.48550/ar...
Article . 2003
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
Bioinformatics
Article . 2005
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Protein secondary structure: entropy, correlations and prediction

Authors: Crooks, Gavin E.; Brenner, Steven E.;

Protein secondary structure: entropy, correlations and prediction

Abstract

Abstract Motivation: Is protein secondary structure primarily determined by local interactions between residues closely spaced along the amino acid backbone or by non-local tertiary interactions? To answer this question, we measure the entropy densities of primary and secondary structure sequences, and the local inter-sequence mutual information density. Results: We find that the important inter-sequence interactions are short ranged, that correlations between neighboring amino acids are essentially uninformative and that only one-fourth of the total information needed to determine the secondary structure is available from local inter-sequence correlations. These observations support the view that the majority of most proteins fold via a cooperative process where secondary and tertiary structure form concurrently. Moreover, existing single-sequence secondary structure prediction algorithms are almost optimal, and we should not expect a dramatic improvement in prediction accuracy. Availability: Both the data sets and analysis code are freely available from our Web site at http://compbio.berkeley.edu/

Keywords

Models, Molecular, Models, Statistical, Sequence Homology, Amino Acid, Entropy, Molecular Sequence Data, Statistics as Topic, Proteins, Biomolecules (q-bio.BM), Markov Chains, Protein Structure, Secondary, Quantitative Biology - Biomolecules, Models, Chemical, Sequence Analysis, Protein, FOS: Biological sciences, Computer Simulation, Amino Acid Sequence, Sequence Alignment, Algorithms

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    65
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
65
Top 10%
Top 10%
Top 10%
Green
gold