• 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