DocumentCode :
2123731
Title :
Pathway-Based Microarray Analysis for Defining Statistical Significant Phenotype-Related Pathways: A Review of Common Approaches
Author :
Misman, M.F. ; Deris, S. ; Hashim, S.Z.M. ; Jumali, R. ; Mohamad, M.S.
Author_Institution :
Dept. of Software Eng., Univ. Teknol. Malaysia, Skudai
fYear :
2009
fDate :
3-5 April 2009
Firstpage :
496
Lastpage :
500
Abstract :
In this review, we have discussed about approaches in pathway based microarray analysis. Commonly, there are two approaches in pathway based analysis, Enrichment Score and Supervised Machine Learning. These pathway based approaches usually aim to statistically define significant pathways that related to phenotypes of interest. Firstly we discussed an overview of pathway based microarray analysis and its general flow processes in scoring the pathways, the methods applied in both approaches, advantages and limitations based on current researches, and pathways database used in pathway analysis. This review aim to provide better understanding about pathway based microarray analysis and its approaches.
Keywords :
biology computing; genetics; lab-on-a-chip; learning (artificial intelligence); statistical analysis; enrichment score; pathway-based microarray gene analysis; statistical significant phenotype; supervised machine learning; Computer science; Cryptography; Feedback circuits; Flip-flops; Information management; Linear feedback shift registers; Random number generation; Random sequences; Shift registers; State feedback; Machine Learning; Microarray; Pathway Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Management and Engineering, 2009. ICIME '09. International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-0-7695-3595-1
Type :
conf
DOI :
10.1109/ICIME.2009.103
Filename :
5077084
Link To Document :
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