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PubMed · 16268788

FASSM: enhanced function association in whole genome analysis using sequence and structural motifs.

Kumar Gaurav·Nitin Gupta·Ramanathan Sowdhamini
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Abstract

We present an algorithm to detect remote homology, which arises through circular permutation and discontinuous domains. It is also helpful in detecting small domain proteins that are characterized by few conserved residues. The input to the algorithm is a set of multiply aligned protein sequence profiles. This method, coded as FASSM, examines the sequence conservation and positions of protein family signatures or motifs for the annotation of protein sequences and to facilitate the analysis of their domains. The overall coverage of FASSM is 93% in comparison to other validation tools like HMM and IMPALA. The method is especially useful for difficult relationships such as discontinuous domains during whole-genome surveys and is demonstrated to perform accurate family associations at sequence identities as low as 15%.

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AlgorithmsAmino Acid MotifsAmino Acid SequenceConserved SequenceDatabases, ProteinEscherichia coli K12GenomicsMethyltransferasesModels, MolecularMolecular Sequence DataNeural Networks, ComputerPhylogenyProteinsProteomicsSequence AlignmentComparative StudyJournal ArticleResearch Support, Non-U.S. Gov't

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Kumar Gaurav, Nitin Gupta, Ramanathan Sowdhamini. 2005. FASSM: enhanced function association in whole genome analysis using sequence and structural motifs.. https://pubmed.ncbi.nlm.nih.gov/16268788/

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