Finding Similar Nucleotide Sequences Using Network BLAST Searches. Issue 1 (27th June 2017)

• Record Type: Journal Article
• Authors: Ladunga, Istvan
• Editors: Bateman, Alex; Pearson, William R.; Stein, Lincoln D.; Stormo, Gary D.; Yates, John R.
• Is Part Of: Current protocols in bioinformatics. Volume 58:Issue 1(2017)
• Page Start: 3.3.1
• Page End: 3.3.25
• Publication Date: 2017-06-27
• Subjects: BLAST -- sequence alignment -- database search -- homology search -- mapping -- nucleic acid -- DNA -- RNA -- genome -- blastn -- Megablast; Bioinformatics -- Laboratory manuals; Nucleotide sequence -- Laboratory manuals; Amino acid sequence -- Laboratory manuals; Base Sequence; Amino Acid Sequence; Computational Biology -- methods; Databases, Genetic; Proteins -- analysis; Sequence Analysis -- methods; Sequence Homology; Amino acid sequence; Bioinformatics; Nucleotide sequence; Laboratory Manuals; Laboratory manuals; 570.285
• DOI: 10.1002/cpbi.29
• Languages: English
• ISSNs: 1934-3396

Abstract

Abstract: The Basic Local Alignment Search Tool (BLAST) is the first tool in the annotation of nucleotide or amino acid sequences. BLAST is a flagship of bioinformatics due to its performance and user‐friendliness. Beginners and intermediate users will learn how to design and submit blastn and Megablast searches on the Web pages at the National Center for Biotechnology Information. We map nucleic acid sequences to genomes, find identical or similar mRNAs, expressed sequence tag, and noncoding RNA sequences, and run Megablast searches, which are much faster than blastn . Understanding results is assisted by taxonomy reports, genomic views, and multiple alignments. We interpret expected frequency thresholds, biological significance, and statistical significance. Weak hits provide no evidence, but indicate hints for further analyses. We find genes that may code for homologous proteins by translated BLAST. We reduce false positives by filtering out low‐complexity regions. Parsed BLAST results can be integrated into analysis pipelines. Links in the output connect to Entrez and PubMed, as well as structural, sequence, interaction, and expression databases. This facilitates integration with a wide spectrum of biological knowledge. © 2017 by John Wiley & Sons, Inc.