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Identifying essential proteins from active PPI networks constructed with dynamic gene expression

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成果类型:
期刊论文
作者:
Xiao, Qianghua;Wang, Jianxin*;Peng, Xiaoqing;Wu, Fang-xiang;Pan, Yi
通讯作者:
Wang, Jianxin
作者机构:
[Peng, Xiaoqing; Xiao, Qianghua; Pan, Yi; Wu, Fang-xiang; Wang, Jianxin] Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China.
[Xiao, Qianghua] Univ South China, Sch Math & Phys, HengYang 421001, Peoples R China.
[Wu, Fang-xiang] Univ Saskatchewan, Div Biomed Engn, Saskatoon, SK S7N 5A9, Canada.
[Pan, Yi] Georgia State Univ, Dept Comp Sci, Atlanta, GA 30302 USA.
通讯机构:
[Wang, Jianxin] C
Cent S Univ, Sch Informat Sci & Engn, Changsha 410083, Hunan, Peoples R China.
语种:
英文
关键词:
Essential proteins;Protein-protein interaction;Dynamic gene expression profiles;Active protein-protein interaction networks;Centrality measures
期刊:
BMC Genomics
ISSN:
1471-2164
年:
2015
卷:
16
期:
3
页码:
1-7
基金类别:
This work is supported in part by the National Natural Science Foundation of China under grant nos. 61232001, 61003124, and 61428209, and Hunan Provincial Innovation Foundation For Postgraduate (CX2013B070), and Science and Technology Plan Projects of Science and Technology Bureau of Hengyang City (grant 2013KJ29).
机构署名:
本校为其他机构
院系归属:
数理学院
摘要:
Essential proteins are vitally important for cellular survival and development, and identifying essential proteins is very meaningful research work in the post-genome era. Rapid increase of available protein-protein interaction (PPI) data has made it possible to detect protein essentiality at the network level. A series of centrality measures have been proposed to discover essential proteins based on the PPI networks. However, the PPI data obtained from large scale, high-throughput experiments generally contain false positives. It is insufficient to use original PPI data to identify essential ...

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