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A Sensitive and Accurate protein domain cLassification Tool (SALT) for short reads
Author(s) -
Yuan Zhang,
Yanni Sun,
James R. Cole
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/btt357
Subject(s) - computer science , domain (mathematical analysis) , contig , source code , annotation , hidden markov model , graph , data mining , computational biology , genome , artificial intelligence , biology , theoretical computer science , gene , genetics , mathematics , programming language , mathematical analysis
Protein domain classification is an important step in functional annotation for next-generation sequencing data. For RNA-Seq data of non-model organisms that lack quality or complete reference genomes, existing protein domain analysis pipelines are applied to short reads directly or to contigs that are generated using de novo sequence assembly tools. However, these strategies do not provide satisfactory performance in classifying short reads into their native domain families.

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