Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractDistinct protocerebral neuropils associated with attractive and aversive female-produced odorants in the male moth brain    Next Abstract"Differentiation of Wines Treated with Wood Chips Based on Their Phenolic Content, Volatile Composition, and Sensory Parameters" »

Bioinformatics


Title:DBRF-MEGN method: an algorithm for deducing minimum equivalent gene networks from large-scale gene expression profiles of gene deletion mutants
Author(s):Kyoda K; Baba K; Onami S; Kitano H;
Address:"Kitano Symbiotic Systems Project, ERATO, Japan Science and Technology Corporation, Shibuya, Tokyo 150-0001, Japan"
Journal Title:Bioinformatics
Year:2004
Volume:20040527
Issue:16
Page Number:2662 - 2675
DOI: 10.1093/bioinformatics/bth306
ISSN/ISBN:1367-4803 (Print) 1367-4803 (Linking)
Abstract:"MOTIVATION: Large-scale gene expression profiles measured in gene deletion mutants are invaluable sources for identifying gene regulatory networks. Signed directed graph (SDG) is the most common representation of gene networks in genetics and cell biology. However, no practical procedure that deduces SDGs 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 SDGs 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 SDGs 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 the prediction of 132 transcriptional targets and modulators of transcriptional activity of 18 transcriptional regulators. AVAILABILITY: The software is available on request"
Keywords:"*Algorithms Gene Deletion Gene Expression Profiling/*methods Gene Expression Regulation/*physiology Models, Biological Mutagenesis, Site-Directed/*genetics Saccharomyces cerevisiae Proteins/*genetics/*metabolism Signal Transduction/*genetics Software;"
Notes:"MedlineKyoda, Koji Baba, Kotaro Onami, Shuichi Kitano, Hiroaki eng Comparative Study Evaluation Study Research Support, Non-U.S. Gov't England 2004/05/29 Bioinformatics. 2004 Nov 1; 20(16):2662-75. doi: 10.1093/bioinformatics/bth306. Epub 2004 May 27"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 22-11-2024