"Gridifying" an evolutionary algorithm for inference of genetic networks using the improved GOGA framework and its performance evaluation on OBI grid

Hiroaki Imade, Naoaki Mizuguchi, Isao Ono, Norihiko Ono, Masahiro Okamoto

Research output: Contribution to journalConference article

9 Citations (Scopus)

Abstract

This paper presents a genetic algorithm running on a grid computing environment for inference of genetic networks. In bioinformatics, inference of genetic networks is one of the most important problems, in which mutual interactions among genes are estimated by using gene-expression time-course data. Network-Structure-Search Evolutionary Algorithm (NSS-EA) is a promising inference method of genetic networks that employs S-system as a model of genetic network and a genetic algorithm (GA) as a search engine. In this paper, we propose an implementation of NSS-EA running on a multi-PC-cluster grid computing environment where multiple PC clusters are connected over the Internet. We "Gridifiy" NSS-EA by using a framework for the development of GAs running on a multi-PC-cluster grid environment, named Grid-Oriented Genetic Algorithm Framework (GOGA Framework). We examined whether the "Gridified" NSS-EA works correctly and evaluated its performance on Open Bioinformatics Grid (OBIGrid) in Japan.

Original languageEnglish
Pages (from-to)171-186
Number of pages16
JournalLecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science)
Volume3370
Publication statusPublished - Oct 17 2005
EventFirst International Workshop on Life Science Grid, LSGRID 2004: Grid Computing in Life Science - Kanazawa, Japan
Duration: May 31 2004Jun 1 2004

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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