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Cascade_scan%3a Mining Signal Transduction Network From High Throughput Data Based On Steepest Descent Method. by Wang%2c Kai
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1CASCADE_SCAN: Mining Signal Transduction Network From High-throughput Data Based On Steepest Descent Method.
By Wang, Kai, Hu, Fuyan, Xu, Kejia, Cheng, Hua, Jiang, Meng, Feng, Ruili, Li, Jing and Wen, Tieqiao
This article is from BMC Bioinformatics , volume 12 . 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/.
“CASCADE_SCAN: Mining Signal Transduction Network From High-throughput Data Based On Steepest Descent Method.” Metadata:
- Title: ➤ CASCADE_SCAN: Mining Signal Transduction Network From High-throughput Data Based On Steepest Descent Method.
- Authors: ➤ Wang, KaiHu, FuyanXu, KejiaCheng, HuaJiang, MengFeng, RuiliLi, JingWen, Tieqiao
- Language: English
Edition Identifiers:
- Internet Archive ID: pubmed-PMC3120702
Downloads Information:
The book is available for download in "texts" format, the size of the file-s is: 13.12 Mbs, the file-s for this book were downloaded 92 times, the file-s went public at Sun Oct 26 2014.
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