Discovering Genes-Diseases Associations From Specialized Literature Using the Grid

Author

Faro, Alberto ; Giordano, Daniela ; Maiorana, Francesco ; Spampinato, Concetto

Author_Institution

Dipt. di Ing. Inf. e Telecomun., Univ. di Catania, Catania, Italy

Volume

13

Issue

4

fYear

2009

fDate

7/1/2009 12:00:00 AM

Firstpage

554

Lastpage

560

Abstract

This paper proposes a novel method for text mining on the Grid, aimed at pointing out hidden relationships for hypothesis generation and suitable for semi-interactive querying. The method is based on unsupervised clustering and the outputs are visualized with contextual information. Grid implementation is crucial for feasibility. We demonstrate it with a mining run for discovering genes-diseases associations from bibliographic sources and annotated databases. The proposed methodology is in view of a Grid architecture specialized in bioinformatics mining tasks. Some performance considerations are provided.

Keywords

bioinformatics; data mining; diseases; genetics; Grid architecture; bioinformatics; data mining; genes-disease associations; Genes-diseases association; Grid; knowledge discovery; text mining; unsupervised clustering; Algorithms; Cluster Analysis; Computational Biology; Cystic Fibrosis; Databases, Bibliographic; Disease; Genetic Predisposition to Disease;

fLanguage

English

Journal_Title

Information Technology in Biomedicine, IEEE Transactions on

Publisher

ieee

ISSN

1089-7771

Type

jour

DOI

10.1109/TITB.2008.2007755

Filename

4663859