Using the gene ontology to enrich biological pathways

Antonio Sanfilippo, Bob Baddeley, Nathaniel Beagley, Jason McDermott, Roderick Riensche, Ronald Taylor, Banu Gopalan

Research output: Contribution to journalReview article

10 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 gene expression data and not independently validated. Alternative approaches use prior biological knowledge to validate automatically inferred pathways, but the prior knowledge is usually not sufficiently tuned to the pathology of focus. 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 and describe an application of this approach to transcriptional data from a mouse model of neuroprotection during stroke.

Original languageEnglish
Pages (from-to)221-235
Number of pages15
JournalInternational journal of computational biology and drug design
Volume2
Issue number3
DOIs
Publication statusPublished - 1 Dec 2009

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Keywords

  • Automatic pathway generation
  • Biological pathways
  • GO
  • Gene ontology
  • Gene similarity
  • Neuroprotection
  • Stroke

ASJC Scopus subject areas

  • Drug Discovery
  • Computer Science Applications

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