File Entry: Identifying Metabolic Pathway within Microarray Gene Expression Data Using Combination of Probabilistic Models

Created: 2012-05-11 02:18:43      Last updated: 2012-05-11 02:18:44
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Version created on: 2012-05-11 02:18:43


Information Description

 Extracting metabolic pathway that dictates a specific biological

response is cunently one of the important disciplines in metabolic system
biology research. Previous methods have successfirlly identified those pathways
but without concerning the genetic effect and relationship of the genes, the
underlying structw€ is not precisely represented and cannot be justified to be
significant biologically. In this article, probabilistic models capable of
identi&ing the significant pathways through metabolic networks that me related
to a specific biologicai response are implemented. This article utilized
combination of two probabilistic models, using ranking clustering and
classification techniques to address limitations of previous methods with the
annotation to Kyoto Encyclopedia of Genes and Genomes (KEGG) to ensure
the pathways are biologically plausible.

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