Metabolic pathway extraction using combined probabilistic models

Abdul Hakim Mohamed Salleh, Mohd Saberi Mohamad

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Extracting metabolic pathway from microarray gene expression data that dictates a specific biological response is currently one of the important disciplines in system biology research. However due to the complexity of the global metabolic network and the importance to maintain the biological structure, this has become a greater challenge. Previous methods have successfully identified those pathways but without concerning the genetic effect and relationship of the genes, representation of the underlying structure is not precise and cannot be justified to be significant biologically. In this article, probabilistic models that are capable of identifying the significant pathways through metabolic networks related to a specific biological response are implemented. This article utilized combination of two probabilistic models to address the limitations of previous methods with the annotation to pathway database to ensure the pathway is biologically plausible.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalInternational Journal of Bio-Science and Bio-Technology
Issue number2
Publication statusPublished - 2012
Externally publishedYes


  • Annotation
  • Biological response
  • Enzymatic reactions
  • Markov model
  • Metabolic pathway
  • Probabilistic models

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Biomedical Engineering
  • Artificial Intelligence


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