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TOM: enhancement and extension of a tool suite for in silico approaches to multigenic hereditary disorders
Author(s) -
D. Masotti,
Christine Nardini,
Simona Rossi,
Elena Bonora,
G. Cara Romeo,
Stefano Volinia,
Luca Benini
Publication year - 2007
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btm588
Subject(s) - in silico , identification (biology) , suite , computer science , hereditary diseases , data mining , computational biology , world wide web , data science , biology , genetics , gene , geography , botany , archaeology
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.

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