| Literature DB >> 18048394 |
Daniele Masotti1, Christine Nardini, Simona Rossi, Elena Bonora, Giovanni Romeo, Stefano Volinia, Luca Benini.
Abstract
UNLABELLED: The study of complex hereditary diseases is a very challenging area of research. The expanding set of in silico approaches offers a flourishing ground for the acceleration of meaningful findings in this area by exploitation of rich and diverse sources of omic data. These approaches are cheap, flexible, extensible, often complementary and can continuously integrate new information and tests to improve the selection of genes responsible for hereditary diseases. Following this principle, we improved and extended our web-service TOM for the identification of candidate genes in the study of complex hereditary diseases. AVAILABILITY: Our tool is freely available online at http://www.micrel.deis.unibo.it/~tom/.Entities:
Mesh:
Year: 2007 PMID: 18048394 DOI: 10.1093/bioinformatics/btm588
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937