A study (PMID: 28158543) published in the July 2017 issue of Bioinformatics collects, classifies and analyzes single nucleotide variants (SNVs) that may affect response to currently approved drugs. They identified 2,640 SNVs of interest, most of which occur rarely in populations (minor allele frequency <0.01).
The researchers used protein sequence alignment tools and mined open data from multiple information resources accessed through E-utilities including PubChem Compound (Kim et al., 2016 PMID: 26400175), NCBI Gene (Maglott D, et al., 2014. PMID: 25355515), NCBI Protein (Sayers, 2013), MMDB (Madej et al., 2012 PMID: 22135289), PDB (Berman et al., 2000 PMID: 10592235), dbSNP (Sherry et al., 2001 PMID: 11125122), and ClinVar (Landrum et al., 2016 PMID: 26582918).
Questions, comments, and other feedback may be sent to Yanli Wang.
Professors, you’re busy – really busy. You have to develop and teach your courses and laboratory sessions, coordinate your lab’s research efforts, write grants and publications, and stay current on everything related to your teaching and research topics.
NCBI has information that would help most of these efforts – but there are so many interesting records and so little time to organize them for efficient use. Sign up for a free NCBI Account and let us help you organize your important lists!
Sign up for an NCBI Account – or sign in to your account if you already have one – and:
Store and automate your searches;
Save and manage collections of important records for use in coursework, research projects and federal grants;
Create public lists for students in your courses and your own Faculty Profile;