Skip Navigation



Bioinformatics Advance Access published online on May 27, 2004
Bioinformatics, doi:10.1093/bioinformatics/bth306
Bioinformatics © Oxford University Press 2004; all rights reserved
This Article
Right arrow Advance Access manuscript (PDF) Freely available
Right arrow All Versions of this Article:
20/16/2662    most recent
bth306v1
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Kyoda, K.
Right arrow Articles by Kitano, H.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kyoda, K.
Right arrow Articles by Kitano, H.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Received September 15, 2003
Revised March 5, 2004
Accepted April 28, 2004

Article

DBRF-MEGN method: an algorithm for deducing minimum equivalent gene networks from large-scale gene expression profiles of gene deletion mutants

Koji Kyoda 1, Kotaro Baba 2, Shuichi Onami 3*, Hiroaki Kitano 4

1 Kitano Symbiotic Systems Project, ERATO, Japan Science and Technology Corporation, M31 6A, 6-31-15 Jingumae, Shibuya, Tokyo 150-0001, Japan; Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku, Yokohama 223-8522, Japan
2 National Institute of Agrobiological Sciences, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8602, Japan; The Systems Biology Institute, M31 6A, 6-31-15 Jingumae, Shibuya, Tokyo 150-0001, Japan
3 Kitano Symbiotic Systems Project, ERATO, Japan Science and Technology Corporation, M31 6A, 6-31-15 Jingumae, Shibuya, Tokyo 150-0001, Japan; Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku, Yokohama 223-8522, Japan; The Systems Biology Institute, M31 6A, 6-31-15 Jingumae, Shibuya, Tokyo 150-0001, Japan
4 Kitano Symbiotic Systems Project, ERATO, Japan Science and Technology Corporation, M31 6A, 6-31-15 Jingumae, Shibuya, Tokyo 150-0001, Japan; Graduate School of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku, Yokohama 223-8522, Japan; The Systems Biology Institute, M31 6A, 6-31-15 Jingumae, Shibuya, Tokyo 150-0001, Japan; Sony Computer Science Laboratories, Inc., 3-14-13 Higashi-Gotanda, Shinagawa, Tokyo 141-0022, Japan

* To whom correspondence should be addressed. E-mail: sonami{at}bio.keio.ac.jp.


  Abstract

Motivation: Large-scale gene expression profiles measured in gene deletion mutants are invaluable sources for identifying gene regulatory networks. Signed directed graph is the most common representation of gene networks in genetics and cell biology. However, no practical procedure that deduces signed directed graphs consistent with such profiles has been developed.

Results: We developed the DBRF-MEGN (difference-based regulation finding-minimum equivalent gene network) method in which an algorithm deduces the most parsimonious signed directed graphs consistent with expression profiles of gene deletion mutants. Positive (or negative) directed edges representing positive (or negative) gene regulations are deduced by comparing the gene expression level between the wild type and mutant. The most parsimonious signed directed graphs are deduced using graph theoretical procedures. Compensation for excess removal of edges by restoring a minimum number of edges makes the method applicable to cyclic gene networks. Use of independent groups of edges greatly reduces the computational cost, thus making the method applicable to large-scale expression profiles. We confirmed the applicability of our method by applying it to the gene expression profiles of 265 Saccharomyces cerevisiae deletion mutants, and we confirmed our method's validity by comparing the pheromone response pathway, general amino acid control system, and copper and iron homeostasis system deduced by our method with those reported in the literature. Interpretation of the gene network deduced from the S. cerevisiae expression profiles by using our method led to prediction of 132 transcriptional targets and modulators of transcriptional activity of 18 transcriptional regulators.

Availability: The software is available on request.

Supplementary Information: http://www.so.bio.keio.ac.jp/dbrf-megn/.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 BioinformaticsHome page
C. Lefebvre, J.-C. Aude, E. Glemet, and C. Neri
Balancing protein similarity and gene co-expression reveals new links between genetic conservation and developmental diversity in invertebrates
Bioinformatics, April 15, 2005; 21(8): 1550 - 1558.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.