Identification of biologically significant elements using correlation networks in high performance computing environments

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

1 Scopus citations

Abstract

Network modeling of high throughput biological data has emerged as a popular tool for analysis in the past decade. Among the many types of networks available, the correlation network model is typically used to represent gene expression data generated via microarray or RNAseq, and many of the structures found within the correlation network have been found to correspond to biological function. The recently described gateway node is a gene that is found structurally to be co-regulated with distinct groups of genes at different conditions or treatments; the resulting structure is typically two clusters connected by one or a few nodes within a multi-state network. As network size and dimensionality grows, however, the methods proposed to identify these gateway nodes require parallelization to remain efficient and computationally feasible. In this research we present our method for identifying gateway nodes in three datasets using a high performance computing environment: quiescence in Saccharomyces cerevisiae, brain aging in Mus Musculus, and the effects of creatine on aging in Mus musculus. We find that our parallel method improves runtime and performs equally as well as sequential approach.

Original languageEnglish (US)
Title of host publicationBioinformatics and Biomedical Engineering - 3rd International Conference, IWBBIO 2015, Proceedings
EditorsFrancisco Ortuño, Ignacio Rojas
PublisherSpringer Verlag
Pages607-619
Number of pages13
ISBN (Electronic)9783319164793
DOIs
StatePublished - 2015
Event3rd International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2015 - Granada, Spain
Duration: Apr 15 2015Apr 17 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9044
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2015
CountrySpain
CityGranada
Period4/15/154/17/15

Keywords

  • Correlation networks
  • Gateway nodes
  • High performance computing
  • Parallel algorithms

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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