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

  • Affiliations:

  • 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

  • Venue:
  • International Journal of Data Mining and Bioinformatics
  • Year:
  • 2014

Quantified Score

Hi-index 0.00

Visualization

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/.