Gene prediction in metagenomic libraries using the self organising map and high performance computing techniques

Nigel McCoy, Shaun Mahony, Aaron Golden

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes a novel approach for annotating metagenomic libraries obtained from environmental samples utilising the self organising map (SOM) neural network formalism. A parallel implementation of the SOM is presented and its particular usefulness in metagenomic annotation highlighted. The benefits of the parallel algorithm and performance increases are explained, the latest results from annotation on an artificially generated metagenomic library presented and the viability of this approach for implementation on existing metagenomic libraries is assessed.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages99-109
Number of pages11
Volume4360 LNBI
StatePublished - 2007
Externally publishedYes
EventDistributed, High-Performance and Grid Computing in Computational Biology International Workshop, GCCB 2006 - Eilat, Israel
Duration: Jan 21 2007Jan 21 2007

Other

OtherDistributed, High-Performance and Grid Computing in Computational Biology International Workshop, GCCB 2006
CountryIsrael
CityEilat
Period1/21/071/21/07

Fingerprint

Computing Methodologies
Metagenomics
Self organizing maps
Self-organizing Map
High Performance
Genes
Gene
Annotation
Computing
Prediction
Parallel algorithms
Parallel Implementation
Neural networks
Viability
Parallel Algorithms
Neural Networks
Libraries

Keywords

  • HPC
  • Metagenomics
  • MPI
  • Self organising map

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

McCoy, N., Mahony, S., & Golden, A. (2007). Gene prediction in metagenomic libraries using the self organising map and high performance computing techniques. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4360 LNBI, pp. 99-109)

Gene prediction in metagenomic libraries using the self organising map and high performance computing techniques. / McCoy, Nigel; Mahony, Shaun; Golden, Aaron.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4360 LNBI 2007. p. 99-109.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

McCoy, N, Mahony, S & Golden, A 2007, Gene prediction in metagenomic libraries using the self organising map and high performance computing techniques. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4360 LNBI, pp. 99-109, Distributed, High-Performance and Grid Computing in Computational Biology International Workshop, GCCB 2006, Eilat, Israel, 1/21/07.
McCoy N, Mahony S, Golden A. Gene prediction in metagenomic libraries using the self organising map and high performance computing techniques. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4360 LNBI. 2007. p. 99-109
McCoy, Nigel ; Mahony, Shaun ; Golden, Aaron. / Gene prediction in metagenomic libraries using the self organising map and high performance computing techniques. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4360 LNBI 2007. pp. 99-109
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