ArticleGenome biology2008
Functionally important segments in proteins dissected using Gene Ontology and geometric clustering of peptide fragments.
Article in Genome biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Unsupervised learning reveals landscape of local structural motifs across protein classes.Bioinformatics (Oxford, England) · 2025Article
- Detecting protein candidate fragments using a structural alphabet profile comparison approach.PloS one · 2013Article
- Dissecting protein loops with a statistical scalpel suggests a functional implication of some structural motifs.BMC bioinformatics · 2011Article
- Detailed analysis of function divergence in a large and diverse domain superfamily: toward a refined protocol of function classification.Structure (London, England : 1993) · 2010Article
- Structural fragment clustering reveals novel structural and functional motifs in alpha-helical transmembrane proteins.BMC bioinformatics · 2010Article
- FragKB: structural and literature annotation resource of conserved peptide fragments and residues.PloS one · 2010Article
- Identification of recurring protein structure microenvironments and discovery of novel functional sites around CYS residues.BMC structural biology · 2010Article
- An atlas of the speed of copy number changes in animal gene families and its implications.PloS one · 2009Article
- Is protein classification necessary? Toward alternative approaches to function annotation.Current opinion in structural biology · 2009Review
- Exploiting structural classifications for function prediction: towards a domain grammar for protein function.Current opinion in structural biology · 2009Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We have developed a geometric clustering algorithm using backbone phi,psi angles to group conformationally similar peptide fragments of any length. By labeling each fragment in the cluster with the level-specific Gene Ontology 'molecular function' term of its protein, we are able to compute statistics for molecular function-propensity and p-value of individual fragments in the cluster. Clustering-cum-statistical analysis for peptide fragments 8 residues in length and with only trans peptide bonds shows that molecular function propensities > or =20 and p-values < or =0.05 can dissect fragments within a protein linked to the molecular function.
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