ArticleNucleic acids research2008
E1DS: catalytic site prediction based on 1D signatures of concurrent conservation.
Article in Nucleic acids research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- CSmetaPred: a consensus method for prediction of catalytic residues.BMC bioinformatics · 2017Article
- Article
- Article
- WildSpan: mining structured motifs from protein sequences.Algorithms for molecular biology : AMB · 2011Article
- Predicting RNA-binding residues from evolutionary information and sequence conservation.BMC genomics · 2010Article
- Networks of high mutual information define the structural proximity of catalytic sites: implications for catalytic residue identification.PLoS computational biology · 2010Article
- seeMotif: exploring and visualizing sequence motifs in 3D structures.Nucleic acids research · 2009Article
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5 authors.
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Abstract
Large-scale automatic annotation of protein sequences remains challenging in postgenomics era. E1DS is designed for annotating enzyme sequences based on a repository of 1D signatures. The employed sequence signatures are derived using a novel pattern mining approach that discovers long motifs consisted of several sequential blocks (conserved segments). Each of the sequential blocks is considerably conserved among the protein members of an EC group. Moreover, a signature includes at least three sequential blocks that are concurrently conserved, i.e. frequently observed together in sequences. In other words, a sequence signature is consisted of residues from multiple regions of the protein sequence, which echoes the observation that an enzyme catalytic site is usually constituted of residues that are largely separated in the sequence. E1DS currently contains 5421 sequence signatures that in total cover 932 4-digital EC numbers. E1DS is evaluated based on a collection of enzymes with catalytic sites annotated in Catalytic Site Atlas. When compared to the famous pattern database PROSITE, predictions based on E1DS signatures are considered more sensitive in identifying catalytic sites and the involved residues. E1DS is available at http://e1ds.ee.ncku.edu.tw/ and a mirror site can be found at http://e1ds.csbb.ntu.edu.tw/.
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