Effective query filtering for fast homology searching.
To improve the accuracy of rapid homology searching it is common practice to filter all queries to mask low complexity regions prior to searching. We show in this paper, through a large-scale study of querying the PIR database, that applying popular filtering techniques unselectively to all queries may reduce retrieval effectiveness. We also show that masking queries with our new technique, cafefilter, which uses the overall distribution of motifs in a database, is at least as effective as current popular query filtering tools in large-scale tests.
Williams
H E
HE
Department of Computer Science, RMIT University, Melbourne, Australia. hugh@cs.rmit.edu.au
D019295:Computational Biology / Q000379:methods; D016208:Databases, Factual; D016678:Genome; D006801:Humans; D011506:Proteins / Q000737:chemistry / Q000235:genetics; D015203:Reproducibility of Results; D016415:Sequence Alignment; D017386:Sequence Homology, Amino Acid; D012689:Sequence Homology, Nucleic Acid; D012984:Software; D014923:Wiskott-Aldrich Syndrome / Q000235:genetics; D051316:Wiskott-Aldrich Syndrome Protein
D011506:Proteins; C495767:WAS protein, human; D051316:Wiskott-Aldrich Syndrome Protein