Genomics Inform Search

CLOSE


Genomics Inform > Volume 6(4); 2008 > Article
DOI: https://doi.org/10.5808/gi.2008.6.4.202   
Biological Pathway Extension Using Microarray Gene Expression Data.
Tae Su Chung, Jihun Kim, Keewon Kim, Ju Han Kim
1Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 110-799, Korea. juhan@snu.ac.kr
2Human Genome Research Institute, Seoul National University College of Medicine, Seoul 110-799, Korea. juhan@snu.ac.kr
Abstract
Biological pathways are known as collections of knowledge of certain biological processes. Although knowledge about a pathway is quite significant to further analysis, it covers only tiny portion of genes that exists. In this paper, we suggest a model to extend each individual pathway using a microarray expression data based on the known knowledge about the pathway. We take the Rosetta compendium dataset to extend pathways of Saccharomyces cerevisiae obtained from KEGG (Kyoto Encyclopedia of genes and genomes) database. Before applying our model, we verify the underlying assumption that microarray data reflect the interactive knowledge from pathway, and we evaluate our scoring system by introducing performance function. In the last step, we validate proposed candidates with the help of another type of biological information. We introduced a pathway extending model using its intrinsic structure and microarray expression data. The model provides the suitable candidate genes for each single biological pathway to extend it.
Keywords: biological pathway; pathway extension; microarray gene expression
TOOLS
Share :
Facebook Twitter Linked In Google+
METRICS Graph View
  • 0 Crossref
  •    
  • 2,385 View
  • 8 Download
Related articles in GNI

Disease Prediction Using Ranks of Gene Expressions.2008 September;6(3)



ABOUT
ARTICLE CATEGORY

Browse all articles >

BROWSE ARTICLES
FOR CONTRIBUTORS
Editorial Office
Room No. 806, 193 Mallijae-ro, Jung-gu, Seoul 04501, Korea
Tel: +82-2-558-9394    Fax: +82-2-558-9434    E-mail: kogo3@kogo.or.kr                

Copyright © 2025 by Korea Genome Organization.

Developed in M2PI

Close layer
prev next