Enhancing automatic biological pathway generation with GO-based gene similarity

Antonio Sanfilippo, Bob Baddeley, Nat Beagley, Rick Riensche, Banu Gopalan

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

4 Citations (Scopus)

Abstract

Most current approaches to automatic pathway generation are based on a reverse engineering approach in which pathway plausibility is solely derived from microarray gene expression data. These approaches tend to lack in generality and offer no independent validation as they are too reliant on the pathway observables that guide pathway generation. By contrast, alternative approaches that use prior biological knowledge to validate pathways inferred from gene expression data may err in the opposite direction as the prior knowledge is usually not sufficiently tuned to the pathology of focus. In this paper, we present a novel pathway generation approach that combines insights from the reverse engineering and knowledge-based approaches to increase the biological plausibility of automatically generated regulatory networks.

Original languageEnglish
Title of host publicationProceedings - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009
Pages448-453
Number of pages6
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009 - Shanghai
Duration: 3 Aug 20095 Aug 2009

Other

Other2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009
CityShanghai
Period3/8/095/8/09

Fingerprint

Reverse engineering
Gene expression
Genes
Pathology
Microarrays

Keywords

  • Automatic pathway generation
  • Biological pathways
  • Gene ontology
  • Gene similarity

ASJC Scopus subject areas

  • Software
  • Biomedical Engineering

Cite this

Sanfilippo, A., Baddeley, B., Beagley, N., Riensche, R., & Gopalan, B. (2009). Enhancing automatic biological pathway generation with GO-based gene similarity. In Proceedings - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009 (pp. 448-453). [5260416] https://doi.org/10.1109/IJCBS.2009.96

Enhancing automatic biological pathway generation with GO-based gene similarity. / Sanfilippo, Antonio; Baddeley, Bob; Beagley, Nat; Riensche, Rick; Gopalan, Banu.

Proceedings - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009. 2009. p. 448-453 5260416.

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

Sanfilippo, A, Baddeley, B, Beagley, N, Riensche, R & Gopalan, B 2009, Enhancing automatic biological pathway generation with GO-based gene similarity. in Proceedings - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009., 5260416, pp. 448-453, 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009, Shanghai, 3/8/09. https://doi.org/10.1109/IJCBS.2009.96
Sanfilippo A, Baddeley B, Beagley N, Riensche R, Gopalan B. Enhancing automatic biological pathway generation with GO-based gene similarity. In Proceedings - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009. 2009. p. 448-453. 5260416 https://doi.org/10.1109/IJCBS.2009.96
Sanfilippo, Antonio ; Baddeley, Bob ; Beagley, Nat ; Riensche, Rick ; Gopalan, Banu. / Enhancing automatic biological pathway generation with GO-based gene similarity. Proceedings - 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing, IJCBS 2009. 2009. pp. 448-453
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