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Infernal 1.1: 100-fold faster RNA homology searches
Author(s) -
Eric P. Nawrocki,
Sean R. Eddy
Publication year - 2013
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/btt509
Subject(s) - computer science , documentation , programming language , software , sequence (biology) , sequence alignment , hidden markov model , computational biology , artificial intelligence , biology , genetics , peptide sequence , gene
Infernal builds probabilistic profiles of the sequence and secondary structure of an RNA family called covariance models (CMs) from structurally annotated multiple sequence alignments given as input. Infernal uses CMs to search for new family members in sequence databases and to create potentially large multiple sequence alignments. Version 1.1 of Infernal introduces a new filter pipeline for RNA homology search based on accelerated profile hidden Markov model (HMM) methods and HMM-banded CM alignment methods. This enables ∼100-fold acceleration over the previous version and ∼10 000-fold acceleration over exhaustive non-filtered CM searches.

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