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 AbstractEffects of baking treatment on the sensory quality and physicochemical properties of green tea with different processing methods    Next AbstractInorganic/organic small molecular semiconductor self-assembly to functional core-shell nanoarchitectures for ultrasensitive chemiresistors to aniline vapor »

BMC Bioinformatics


Title:CASCADE_SCAN: mining signal transduction network from high-throughput data based on steepest descent method
Author(s):Wang K; Hu F; Xu K; Cheng H; Jiang M; Feng R; Li J; Wen T;
Address:"Laboratory of Molecular Neurobiology, School of Life Sciences and Institute of Systems Biology, Shanghai University, Shanghai 200444, China"
Journal Title:BMC Bioinformatics
Year:2011
Volume:20110517
Issue:
Page Number:164 -
DOI: 10.1186/1471-2105-12-164
ISSN/ISBN:1471-2105 (Electronic) 1471-2105 (Linking)
Abstract:"BACKGROUND: Signal transduction is an essential biological process involved in cell response to environment changes, by which extracellular signaling initiates intracellular signaling. Many computational methods have been generated in mining signal transduction networks with the increasing of high-throughput genomic and proteomic data. However, more effective means are still needed to understand the complex mechanisms of signaling pathways. RESULTS: We propose a new approach, namely CASCADE_SCAN, for mining signal transduction networks from high-throughput data based on the steepest descent method using indirect protein-protein interactions (PPIs). This method is useful for actual biological application since the given proteins utilized are no longer confined to membrane receptors or transcription factors as in existing methods. The precision and recall values of CASCADE_SCAN are comparable with those of other existing methods. Moreover, functional enrichment analysis of the network components supported the reliability of the results. CONCLUSIONS: CASCADE_SCAN is a more suitable method than existing methods for detecting underlying signaling pathways where the membrane receptors or transcription factors are unknown, providing significant insight into the mechanism of cellular signaling in growth, development and cancer. A new tool based on this method is freely available at http://www.genomescience.com.cn/CASCADE_SCAN/"
Keywords:Computational Biology/*methods Feedback Pheromones/metabolism Proteins/*isolation & purification/metabolism Proteomics/*methods *Signal Transduction Yeasts/metabolism;
Notes:"MedlineWang, Kai Hu, Fuyan Xu, Kejia Cheng, Hua Jiang, Meng Feng, Ruili Li, Jing Wen, Tieqiao eng Research Support, Non-U.S. Gov't England 2011/05/18 BMC Bioinformatics. 2011 May 17; 12:164. doi: 10.1186/1471-2105-12-164"

 
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 05-12-2024