Assignment of protein sequences to existing domain and family classification systems: Pfam and the PDB
Author(s) -
Qifang Xu,
Roland L. Dunbrack
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts533
Subject(s) - protein data bank (rcsb pdb) , protein data bank , computer science , domain (mathematical analysis) , sequence alignment , identifier , set (abstract data type) , protein domain , data mining , protein family , hidden markov model , structural classification of proteins database , computational biology , protein structure , artificial intelligence , genetics , biology , peptide sequence , mathematics , gene , mathematical analysis , biochemistry , programming language
Automating the assignment of existing domain and protein family classifications to new sets of sequences is an important task. Current methods often miss assignments because remote relationships fail to achieve statistical significance. Some assignments are not as long as the actual domain definitions because local alignment methods often cut alignments short. Long insertions in query sequences often erroneously result in two copies of the domain assigned to the query. Divergent repeat sequences in proteins are often missed.
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