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 AbstractPupal mortality and adult emergence of western cherry fruit fly (Diptera: Tephritidae) exposed to the fungus Muscodor albus (Xylariales: Xylariaceae)    Next Abstract"Spindle dynamics and cell cycle regulation of dynein in the budding yeast, Saccharomyces cerevisiae" »

ScientificWorldJournal


Title:Pathway detection from protein interaction networks and gene expression data using color-coding methods and A * search algorithms
Author(s):Yeh CY; Yeh HY; Arias CR; Soo VW;
Address:"Department of Computer Science, National Tsing Hua University, Hsinchu 300, Taiwan"
Journal Title:ScientificWorldJournal
Year:2012
Volume:20120401
Issue:
Page Number:315797 -
DOI: 10.1100/2012/315797
ISSN/ISBN:1537-744X (Electronic) 2356-6140 (Print) 1537-744X (Linking)
Abstract:"With the large availability of protein interaction networks and microarray data supported, to identify the linear paths that have biological significance in search of a potential pathway is a challenge issue. We proposed a color-coding method based on the characteristics of biological network topology and applied heuristic search to speed up color-coding method. In the experiments, we tested our methods by applying to two datasets: yeast and human prostate cancer networks and gene expression data set. The comparisons of our method with other existing methods on known yeast MAPK pathways in terms of precision and recall show that we can find maximum number of the proteins and perform comparably well. On the other hand, our method is more efficient than previous ones and detects the paths of length 10 within 40 seconds using CPU Intel 1.73 GHz and 1 GB main memory running under windows operating system"
Keywords:"*Algorithms Animals Color Computational Biology Databases, Protein Fungal Proteins/genetics *Gene Expression Regulation, Fungal *Gene Expression Regulation, Neoplastic Genes, Fungal Genes, Neoplasm Humans Male Pheromones/metabolism Prostatic Neoplasms/*ge;"
Notes:"MedlineYeh, Cheng-Yu Yeh, Hsiang-Yuan Arias, Carlos Roberto Soo, Von-Wun eng Research Support, Non-U.S. Gov't 2012/05/12 ScientificWorldJournal. 2012; 2012:315797. doi: 10.1100/2012/315797. Epub 2012 Apr 1"

 
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 26-12-2024