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CASCADE_SCAN: mining signal transduction network from high-throughput data based on steepest descent method
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-t...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3120702/ https://www.ncbi.nlm.nih.gov/pubmed/21575263 http://dx.doi.org/10.1186/1471-2105-12-164 |
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author | Wang, Kai Hu, Fuyan Xu, Kejia Cheng, Hua Jiang, Meng Feng, Ruili Li, Jing Wen, Tieqiao |
author_facet | Wang, Kai Hu, Fuyan Xu, Kejia Cheng, Hua Jiang, Meng Feng, Ruili Li, Jing Wen, Tieqiao |
author_sort | Wang, Kai |
collection | PubMed |
description | 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/. |
format | Online Article Text |
id | pubmed-3120702 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31207022011-06-23 CASCADE_SCAN: mining signal transduction network from high-throughput data based on steepest descent method Wang, Kai Hu, Fuyan Xu, Kejia Cheng, Hua Jiang, Meng Feng, Ruili Li, Jing Wen, Tieqiao BMC Bioinformatics Research Article 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/. BioMed Central 2011-05-17 /pmc/articles/PMC3120702/ /pubmed/21575263 http://dx.doi.org/10.1186/1471-2105-12-164 Text en Copyright ©2011 Wang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wang, Kai Hu, Fuyan Xu, Kejia Cheng, Hua Jiang, Meng Feng, Ruili Li, Jing Wen, Tieqiao CASCADE_SCAN: mining signal transduction network from high-throughput data based on steepest descent method |
title | CASCADE_SCAN: mining signal transduction network from high-throughput data based on steepest descent method |
title_full | CASCADE_SCAN: mining signal transduction network from high-throughput data based on steepest descent method |
title_fullStr | CASCADE_SCAN: mining signal transduction network from high-throughput data based on steepest descent method |
title_full_unstemmed | CASCADE_SCAN: mining signal transduction network from high-throughput data based on steepest descent method |
title_short | CASCADE_SCAN: mining signal transduction network from high-throughput data based on steepest descent method |
title_sort | cascade_scan: mining signal transduction network from high-throughput data based on steepest descent method |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3120702/ https://www.ncbi.nlm.nih.gov/pubmed/21575263 http://dx.doi.org/10.1186/1471-2105-12-164 |
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