Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

H2rs: deducing evolutionary and functionally important residue positions by means of an entropy and similarity based analysis of multiple sequence alignments.

BMC bioinformatics - 27 Apr 2014

Janda Jan-Oliver, Popal Ajmal, Bauer Jochen, Busch Markus, Klocke Michael, Spitzer Wolfgang, Keller Jörg, Merkl Rainer

Abstract excerpt

BACKGROUND: The identification of functionally important residue positions is an important task of computational biology. Methods of correlation analysis allow for the identification of pairs of residue positions, whose occupancy is mutually dependent due to constraints imposed by protein structure or function. A common measure assessing these dependencies is the mutual information, which is based on Shannon's...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Algorithms
Share to Amino Acids

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Computer Simulation

Share to Enzymes

Share to Evolution, Molecular

Share to Protein Conformation

Share to Proteins

Share to Sequence Alignment

Source

Open in PubMed Open full text

Identifiers

PMID: 24766829
DOI: 10.1186/1471-2105-15-118
PMCID: PMC4021312

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

H2rs: deducing evolutionary and functionally important residue positions by means of an entropy and similarity based analysis of multiple sequence alignments.PMID 24766829Read ↗

Prediction of disulfide connectivity in proteins with machine-learning methods and correlated mutations.Semantic proximity Read ↗

Contact prediction using mutual information and neural nets.Semantic proximity Read ↗

Mapping the mutual information network of enzymatic families in the protein structure to unveil functional features.Semantic proximity Read ↗

Experimental assessment of the importance of amino acid positions identified by an entropy-based correlation analysis of multiple-sequence alignments.Semantic proximity Read ↗

Identifying relevant positions in proteins by Critical Variable Selection.Semantic proximity Read ↗

Evolutionary couplings and sequence variation effect predict protein binding sites.Semantic proximity Read ↗

Using information theory to search for co-evolving residues in proteins.Semantic proximity Read ↗

PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments.Semantic proximity Read ↗

Predicting protein β-sheet contacts using a maximum entropy-based correlated mutation measure.Semantic proximity Read ↗

Optimal data collection for correlated mutation analysis.Semantic proximity Read ↗

Sibe: a computation tool to apply protein sequence statistics to folding and designSemantic proximity Read ↗

Functional and Early Folding Residues are separated in proteins to increase evolvability and robustnessSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.