On the design of advanced filters for biological networks using graph theoretic properties

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

1 Scopus citations

Abstract

Network modeling of biological systems is a powerful tool for analysis of high-throughput datasets by computational systems biologists. Integration of networks to form a heterogeneous model requires that each network be as noise-free as possible while still containing relevant biological information. In earlier work, we have shown that the graph theoretic properties of gene correlation networks can be used to highlight and maintain important structures such as high degree nodes, clusters, and critical links between sparse network branches while reducing noise. In this paper, we propose the design of advanced network filters using structurally related graph theoretic properties. While spanning trees and chordal subgraphs provide filters with special advantages, we hypothesize that a hybrid subgraph sampling method will allow for the design of a more effective filter preserving key properties in biological networks. That the proposed approach allows us to optimize a number of parameters associated with the filtering process which in turn improves upon the identification of essential genes in mouse aging networks.

Original languageEnglish (US)
Title of host publicationProceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012
Pages556-560
Number of pages5
DOIs
StatePublished - 2012
Event2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM2012 - Philadelphia, PA, United States
Duration: Oct 4 2012Oct 7 2012

Publication series

NameProceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012

Conference

Conference2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM2012
CountryUnited States
CityPhiladelphia, PA
Period10/4/1210/7/12

Keywords

  • biological networks
  • chordal graphs
  • clusters
  • hubs
  • lethal genes
  • network filters
  • spanning tree

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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  • Cite this

    Dempsey, K., Chen, T. Y., Bhowmick, S., & Ali, H. (2012). On the design of advanced filters for biological networks using graph theoretic properties. In Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012 (pp. 556-560). [6392617] (Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2012). https://doi.org/10.1109/BIBM.2012.6392617