Title: Identifying significant associations of orthologous simple sequence repeats with gene ontologies

Authors: Chien-Ming Chen; Tun-Wen Pai; Chia-Sheng Chuang; Jhen-Li Huang; Wen-Shyong Tzou; Chin-Hua Hu

Addresses: Department of Computer Science and Engineering, National Taiwan Ocean University, No. 2, Pei-Ning Road, Keelung, Taiwan 20224, ROC ' Department of Computer Science and Engineering, National Taiwan Ocean University, No. 2, Pei-Ning Road, Keelung, Taiwan 20224, ROC ' Department of Computer Science and Engineering, National Taiwan Ocean University, No. 2, Pei-Ning Road, Keelung, Taiwan 20224, ROC ' Department of Computer Science and Engineering, National Taiwan Ocean University, No. 2, Pei-Ning Road, Keelung, Taiwan 20224, ROC ' Department of Life Sciences and Center of Excellence for Marine Bioenvironment and Biotechnology, National Taiwan Ocean University, No. 2, Pei-Ning Road, Keelung, Taiwan 20224, ROC ' Department of Life Sciences and Center of Excellence for Marine Bioenvironment and Biotechnology, National Taiwan Ocean University, No. 2, Pei-Ning Road, Keelung, Taiwan 20224, ROC

Abstract: Simple Sequence Repeats (SSRs), also known as microsatellites, regulate gene functions. SSR mutations in a disease gene may cause various genetic disorders. To identify putative functional SSRs, a web-based system, Gene Ontology SSR Hierarchy (GOSH), was developed to facilitate discovery of significant associations between SSRs and Gene Ontology (GO) terms. Using the GO hierarchy term structure, GOSH assists users with selecting functional or biological gene subsets. Significant SSR patterns are retrieved and identified via comprehensive overrepresentation analysis within a target gene subset and by comparing results with orthologous genes. Pattern relationships between different biological subsets or supersets can be observed by using the GO hierarchy structure directly. GOSH also supports GO searching through identified significant SSR patterns and all GO terms possessing such patterns are listed for consultation. GOSH is the first comprehensive and efficient online mining tool for discovering significant orthologous SSR patterns in GO terms and is available at http:/&/gosh.cs.ntou.edu.tw/.

Keywords: orthology; gene ontologies; biomarkers; simple sequence repeats; SSR patterns; microsatellites; homologous genes; comparative genomics; bioinformatics; web-based systems; data mining.

DOI: 10.1504/IJDMB.2014.057781

International Journal of Data Mining and Bioinformatics, 2014 Vol.9 No.1, pp.37 - 51

Received: 16 Feb 2012
Accepted: 02 Mar 2012
Published online: 21 Oct 2014 *

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