Abstract:
BACKGROUND:Here we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. RESULTS:In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resulting functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. CONCLUSIONS:PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/. PSAT stands apart from other sequence-based genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.
journal_name
BMC Bioinformaticsjournal_title
BMC bioinformaticsauthors
Leung E,Huang A,Cadag E,Montana A,Soliman JL,Zhou CLdoi
10.1186/s12859-016-0887-ysubject
Has Abstractpub_date
2016-01-20 00:00:00pages
43issn
1471-2105pii
10.1186/s12859-016-0887-yjournal_volume
17pub_type
杂志文章abstract:BACKGROUND:Protein structure comparison is a fundamental task in structural biology. While the number of known protein structures has grown rapidly over the last decade, searching a large database of protein structures is still relatively slow using existing methods. There is a need for new techniques which can rapidly...
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更新日期:2004-09-30 00:00:00
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