Web tools for the prioritization of candidate disease genes

Oti, Martin, Ballouz, Sara and Wouters, Merridee A. 2011, Web tools for the prioritization of candidate disease genes, in In silico tools for gene discovery, Humana Press, New York, N.Y., pp.189-206.

Attached Files
Name Description MIMEType Size Downloads

Title Web tools for the prioritization of candidate disease genes
Author(s) Oti, Martin
Ballouz, Sara
Wouters, Merridee A.
Title of book In silico tools for gene discovery
Editor(s) Yu, Bing
Hinchcliffe, Marcus
Publication date 2011
Series Methods in molecular biology
Chapter number 12
Total chapters 21
Start page 189
End page 206
Total pages 18
Publisher Humana Press
Place of Publication New York, N.Y.
Keyword(s) bioinformatics
disease gene prediction
disease gene prioritization
genetic diseases
genome
phenotype
Summary Despite increasing sequencing capacity, genetic disease investigation still frequently results in the identification of loci containing multiple candidate disease genes that need to be tested for involvement in the disease. This process can be expedited by prioritizing the candidates prior to testing. Over the last decade, a large number of computational methods and tools have been developed to assist the clinical geneticist in prioritizing candidate disease genes. In this chapter, we give an overview of computational tools that can be used for this purpose, all of which are freely available over the web.
ISBN 9781617791758
ISSN 1064-3745
Language eng
Field of Research 060102 Bioinformatics
Socio Economic Objective 920110 Inherited Diseases (incl. Gene Therapy)
HERDC Research category B1 Book chapter
HERDC collection year 2011
Copyright notice ©2011, Springer
Persistent URL http://hdl.handle.net/10536/DRO/DU:30043167

Document type: Book Chapter
Collection: School of Life and Environmental Sciences
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 3 times in TR Web of Science
Scopus Citation Count Cited 5 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 74 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Tue, 13 Mar 2012, 09:50:18 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.