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A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks
The genetic, proteomic, disease and pharmacological studies have generated rich data in protein interaction, disease regulation and drug activities useful for systems-level study of the biological, disease and drug therapeutic processes. These studies are facilitated by the established and the emerg...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862332/ https://www.ncbi.nlm.nih.gov/pubmed/27542402 http://dx.doi.org/10.1093/bib/bbw071 |
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author | Zhang, Peng Tao, Lin Zeng, Xian Qin, Chu Chen, Shangying Zhu, Feng Li, Zerong Jiang, Yuyang Chen, Weiping Chen, Yu-Zong |
author_facet | Zhang, Peng Tao, Lin Zeng, Xian Qin, Chu Chen, Shangying Zhu, Feng Li, Zerong Jiang, Yuyang Chen, Weiping Chen, Yu-Zong |
author_sort | Zhang, Peng |
collection | PubMed |
description | The genetic, proteomic, disease and pharmacological studies have generated rich data in protein interaction, disease regulation and drug activities useful for systems-level study of the biological, disease and drug therapeutic processes. These studies are facilitated by the established and the emerging computational methods. More recently, the network descriptors developed in other disciplines have become more increasingly used for studying the protein–protein, gene regulation, metabolic, disease networks. There is an inadequate coverage of these useful network features in the public web servers. We therefore introduced upto 313 literature-reported network descriptors in PROFEAT web server, for describing the topological, connectivity and complexity characteristics of undirected unweighted (uniform binding constants and molecular levels), undirected edge-weighted (varying binding constants), undirected node-weighted (varying molecular levels), undirected edge-node-weighted (varying binding constants and molecular levels) and directed unweighted (oriented process) networks. The usefulness of the PROFEAT computed network descriptors is illustrated by their literature-reported applications in studying the protein–protein, gene regulatory, gene co-expression, protein–drug and metabolic networks. PROFEAT is accessible free of charge at http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi. |
format | Online Article Text |
id | pubmed-5862332 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-58623322018-09-04 A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks Zhang, Peng Tao, Lin Zeng, Xian Qin, Chu Chen, Shangying Zhu, Feng Li, Zerong Jiang, Yuyang Chen, Weiping Chen, Yu-Zong Brief Bioinform Papers The genetic, proteomic, disease and pharmacological studies have generated rich data in protein interaction, disease regulation and drug activities useful for systems-level study of the biological, disease and drug therapeutic processes. These studies are facilitated by the established and the emerging computational methods. More recently, the network descriptors developed in other disciplines have become more increasingly used for studying the protein–protein, gene regulation, metabolic, disease networks. There is an inadequate coverage of these useful network features in the public web servers. We therefore introduced upto 313 literature-reported network descriptors in PROFEAT web server, for describing the topological, connectivity and complexity characteristics of undirected unweighted (uniform binding constants and molecular levels), undirected edge-weighted (varying binding constants), undirected node-weighted (varying molecular levels), undirected edge-node-weighted (varying binding constants and molecular levels) and directed unweighted (oriented process) networks. The usefulness of the PROFEAT computed network descriptors is illustrated by their literature-reported applications in studying the protein–protein, gene regulatory, gene co-expression, protein–drug and metabolic networks. PROFEAT is accessible free of charge at http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi. Oxford University Press 2017-11 2016-08-18 /pmc/articles/PMC5862332/ /pubmed/27542402 http://dx.doi.org/10.1093/bib/bbw071 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Papers Zhang, Peng Tao, Lin Zeng, Xian Qin, Chu Chen, Shangying Zhu, Feng Li, Zerong Jiang, Yuyang Chen, Weiping Chen, Yu-Zong A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks |
title | A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks |
title_full | A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks |
title_fullStr | A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks |
title_full_unstemmed | A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks |
title_short | A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks |
title_sort | protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks |
topic | Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862332/ https://www.ncbi.nlm.nih.gov/pubmed/27542402 http://dx.doi.org/10.1093/bib/bbw071 |
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