Universiti Teknologi Malaysia Institutional Repository

Identifying metabolic pathway within microarray gene expression data using combination of probabilistic models

Mohamed Salleh, Abdul Hakim and Mohammad, Mohd. Saberi (2012) Identifying metabolic pathway within microarray gene expression data using combination of probabilistic models. In: Communications in Computer and Information Science. Springer-Verlag., Berlin, pp. 52-61. ISBN 978-364232825-1

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Official URL: http://dx.doi.org/10.1007/978-3-642-32826-8_6

Abstract

Extracting metabolic pathway that dictates a specific biological response is currently one of the important disciplines in metabolic system biology research. Previous methods have successfully identified those pathways but without concerning the genetic effect and relationship of the genes, the underlying structure is not precisely represented and cannot be justified to be significant biologically. In this article, probabilistic models capable of identifying the significant pathways through metabolic networks that are related to a specific biological 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.

Item Type:Book Section
Additional Information:Indexed by Scopus
Uncontrolled Keywords:annotation, biological response, metabolic pathway, probabilistic models
Subjects:Q Science > Q Science (General)
Divisions:Computer Science and Information System
ID Code:35807
Deposited By:INVALID USER
Deposited On:11 Nov 2013 09:46
Last Modified:02 Feb 2017 05:55

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