The global trace graph, a novel paradigm for searching protein sequence databases
Author(s) -
Andreas Heger,
Swapan Mallick,
Christopher Wilton,
Liisa Holm
Publication year - 2007
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/btm358
Subject(s) - leverage (statistics) , computer science , sequence alignment , sequence (biology) , cluster analysis , sequence database , computational biology , graph , alignment free sequence analysis , data mining , bioinformatics , biology , artificial intelligence , peptide sequence , theoretical computer science , genetics , gene
Propagating functional annotations to sequence-similar, presumably homologous proteins lies at the heart of the bioinformatics industry. Correct propagation is crucially dependent on the accurate identification of subtle sequence motifs that are conserved in evolution. The evolutionary signal can be difficult to detect because functional sites may consist of non-contiguous residues while segments in-between may be mutated without affecting fold or function.
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