This HTML5 document contains 20 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Subject Item

n2:w

rdf:type

bibo:Article rdac:C10001

dcterms:isPartOf

n11:w

dcterms:subject

n6:computationalbiology

dcterms:title

The identification of complete domains within protein sequences using accurate E-values for semi-global alignment

rdaw:P10072

n14:print n14:web

vivo:relatedBy

n10:3 n10:1 n10:2 n10:4 n10:5

marcrel:aut

n4:82d73b0275437b3393339773ed393a59 n2:sheetlinsergeyl n2:bryantstephenh n2:parkyonil n2:kannmaricelg

dcterms:abstract

The sequencing of complete genomes has created a pressing need for automated annotation of gene function. Because domains are the basic units of protein function and evolution, a gene can be annotated from a domain database by aligning domains to the corresponding protein sequence. Ideally, complete domains are aligned to protein subsequences, in a ‘semi-global alignment’. Local alignment, which aligns pieces of domains to subsequences, is common in high-throughput annotation applications, however. It is a mature technique, with the heuristics and accurate E-values required for screening large databases and evaluating the screening results. Hidden Markov models (HMMs) provide an alternative theoretical framework for semi-global alignment, but their use is limited because they lack heuristic acceleration and accurate E-values. Our new tool, GLOBAL, overcomes some limitations of previous semi-global HMMs: it has accurate E-values and the possibility of the heuristic acceleration required for high-throughput applications. Moreover, according to a standard of truth based on protein structure, two semi-global HMM alignment tools (GLOBAL and HMMer) had comparable performance in identifying complete domains, but distinctly outperformed two tools based on local alignment. When searching for complete protein domains, therefore, GLOBAL avoids disadvantages commonly associated with HMMs, yet maintains their superior retrieval performance.

hub:articleType

n8:researcharticle

hub:isPartOfThisJournal

n15:w