By Topic

Discovery and assessment of gene-disease associations by integrated analysis of scientific literature and microarray data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Alberto Faro ; Department of Informatics and Telecommunication Engineering, University of Catania, 95125, Italy ; Daniela Giordano ; Concetto Spampinato

The paper outlines a methodology and presents a tool to help biomedical researchers in interpreting complex experiments by automatically discovering gene networks and underlying biological processes (revealed by gene-expression patterns) that usually are extracted manually using existing tools. The proposed method, first, starts by mining specialized medical literature available on the Web to discover possible associations between genes and diseases. Discovered gene-disease associations are subsequently explored by analyzing abnormally expressed genes using microarray data analysis. Afterwards, relevant gene networks are built by clustering these genes on the basis of the similarity of their profile expressions in microarrays data. Finally, molecular, biological processes, cellular components and molecular functions, which may have a role in the disease, are pointed out by querying the Gene Ontology (GO) database. The methodology is illustrated by a case study on neuromuscular disorders.

Published in:

Proceedings of the 10th IEEE International Conference on Information Technology and Applications in Biomedicine

Date of Conference:

3-5 Nov. 2010