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Nucleic Acids Research Advance Access published online on September 7, 2007
Nucleic Acids Research, doi:10.1093/nar/gkm659
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© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Database Issue

MutDB: update on development of tools for the biochemical analysis of genetic variation

Arti Singh1, Adebayo Olowoyeye1, Peter H. Baenziger1, Jessica Dantzer1, Maricel G. Kann2, Predrag Radivojac3, Randy Heiland4 and Sean D. Mooney1,*

1Center for Computational Biology and Bioinfomatics, Department of Medical and Molecular Genetics, Indiana University School of Medicine; 410 W. 10th Street, Suite 5000, Indianapolis, IN 46202, 2Department of Biological Sciences, University of Maryland Baltimore County, Baltimore, MD 21250, 3School of Informatics, Indiana University; 1900 East 10th Street, Bloomington, IN 47406 and 4Pervasive Technology Labs, Indiana University; Informatics and Communications Technology Complex, 535 West Michigan Street, Indianapolis, IN 46202, USA

*To whom correspondance should be addressed. Tel: +1 317 278 9221; Fax: +1 317 278 9217; Email: mooney{at}compbio.iupui.edu

Received February 6, 2007. Revised August 9, 2007. Accepted August 9, 2007.

Understanding how genetic variation affects the molecular function of gene products is an emergent area of bioinformatic research. Here, we present updates to MutDB (http://www.mutdb.org), a tool aiming to aid bioinformatic studies by integrating publicly available databases of human genetic variation with molecular features and clinical phenotype data. MutDB, first developed in 2002, integrates annotated SNPs in dbSNP and amino acid substitutions in Swiss-Prot with protein structural information, links to scores that predict functional disruption and other useful annotations. Though these functional annotations are mainly focused on nonsynonymous SNPs, some information on other SNP types included in dbSNP is also provided. Additionally, we have developed a new functionality that facilitates KEGG pathway visualization of genes containing SNPs and a SNP query tool for visualizing and exporting sets of SNPs that share selected features based on certain filters.


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