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Blocks‐based methods for detecting protein homology
Author(s) -
Henikoff Jorja G.,
Pietrokovski Shmuel,
McCallum Claire M.,
Henikoff Steven
Publication year - 2000
Publication title -
electrophoresis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.666
H-Index - 158
eISSN - 1522-2683
pISSN - 0173-0835
DOI - 10.1002/(sici)1522-2683(20000501)21:9<1700::aid-elps1700>3.0.co;2-v
Subject(s) - protein data bank (rcsb pdb) , phylogenetic tree , computational biology , sequence alignment , computer science , sequence database , homology (biology) , block (permutation group theory) , protein data bank , multiple sequence alignment , sequence homology , information retrieval , database , protein structure , data mining , biology , genetics , dna , peptide sequence , gene , base sequence , combinatorics , mathematics , biochemistry
The most highly conserved regions of proteins can be represented as blocks of aligned sequence segments, typically with multiple blocks for a given protein family. The Blocks Database World Wide Web (http://blocks.fhcrc.org) and e-mail (blocks@blocks. fhcrc.org) servers provide tools to search DNA and protein queries against the Blocks+ Database of multiple alignments. We describe features for detection of distant relationships using blocks. Blocks+ includes protein families from the PROSITE, Prints, Pfam-A, ProDom and Domo databases. Other features include searching Blocks+ with the BLIMPS and NCBI's IMPALA programs, sequence logos, phylogenetic trees, three-dimensional display of blocks on PDB structures, and a polymerase chain reaction (PCR) primer design strategy based on blocks.