An integrated approach to predictive genomic analytics

Jason E. McDermott, Bob Baddeley, Susan Stevens, Antonio Sanfilippo, Rick Riensche, Mary Stenzel-Poore, Ronald Taylor, Russ Jensen

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

1 Citation (Scopus)

Abstract

A variety of methods and algorithms have recently been employed in the analysis of gene expression data, including reverseengineering and knowledge-based pathway modeling, semantic gene similarity, network analysis and clustering. These methods and algorithms address different subparts of the same overall challenge and need to be applied in combination to address predictive genomic analysis as a whole. In this paper, we present an integrated approach to predictive genomic analysis that achieves this objective and describe an application of the approach to the study of neuroprotection in stroke.

Original languageEnglish
Title of host publication2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
Pages390-393
Number of pages4
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 - Niagara Falls, NY
Duration: 2 Aug 20104 Aug 2010

Other

Other2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
CityNiagara Falls, NY
Period2/8/104/8/10

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Keywords

  • Biological pathways
  • Gene clustering
  • Gene ontology
  • Gene similarity
  • Pathway inference
  • Predictive pathway analysis

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Information Management

Cite this

McDermott, J. E., Baddeley, B., Stevens, S., Sanfilippo, A., Riensche, R., Stenzel-Poore, M., Taylor, R., & Jensen, R. (2010). An integrated approach to predictive genomic analytics. In 2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 (pp. 390-393) https://doi.org/10.1145/1854776.1854837