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Tsinghua Science and Technology 2020, 25(4): 542-552 https://doi.org/10.26599/TST.2019.9010056
Open Access | Issue | Published: 13 January 2020

NetEPD: A Network-Based Essential Protein Discovery Platform

Show Author's Information Jiashuai Zhang,  Wenkai Li,  Min Zeng,  Xiangmao Meng,  Lukasz Kurgan,  Fang-Xiang Wu,  Min Li( )
School of Computer Science and Engineering, Central South University, Changsha 410083, China.
Department of Computer Science, Virginia Common-wealth University, Richmond, VA 23284-2512, USA.
Division of Biomedical Engineering and Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, S7N 5A9, Canada.
Keywords:
visualization, essential proteins, centrality, data integration, evaluation
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Zhang J, Li W, Zeng M, et al. NetEPD: A Network-Based Essential Protein Discovery Platform. Tsinghua Science and Technology, 2020, 25(4): 542-552. https://doi.org/10.26599/TST.2019.9010056
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Abstract Full text About this article

Proteins drive virtually all cellular-level processes. The proteins that are critical to cell proliferation and survival are defined as essential. These essential proteins are implicated in key metabolic and regulatory networks, and are important in the context of rational drug design efforts. The computational identification of the essential proteins benefits from the proliferation of publicly available protein interaction datasets. Scientists have developed several algorithms that use these interaction datasets to predict essential proteins. However, a comprehensive web platform that facilitates the analysis and prediction of essential proteins is missing. In this study, we design, implement, and release NetEPD: a network-based essential protein discovery platform. This resource integrates data on Protein-Protein Interaction (PPI) networks, gene expression, subcellular localization, and a native set of essential proteins. It also computes a variety of node centrality measures, evaluates the predictions of essential proteins, and visualizes PPI networks. This comprehensive platform functions by implementing four activities, which include the collection of datasets, computation of centrality measures, evaluation, and visualization. The results produced by NetEPD are visualized on its website, and sent to a user-provided email, and they are available to download in a parsable format. This platform is freely available at http://bioinformatics.csu.edu.cn/netepd.


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About this article

NetEPD: A Network-Based Essential Protein Discovery Platform

Show Author's information Jiashuai Zhang, Wenkai Li, Min Zeng, Xiangmao Meng, Lukasz Kurgan, Fang-Xiang Wu, Min Li( )
School of Computer Science and Engineering, Central South University, Changsha 410083, China.
Department of Computer Science, Virginia Common-wealth University, Richmond, VA 23284-2512, USA.
Division of Biomedical Engineering and Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, S7N 5A9, Canada.

Abstract

Proteins drive virtually all cellular-level processes. The proteins that are critical to cell proliferation and survival are defined as essential. These essential proteins are implicated in key metabolic and regulatory networks, and are important in the context of rational drug design efforts. The computational identification of the essential proteins benefits from the proliferation of publicly available protein interaction datasets. Scientists have developed several algorithms that use these interaction datasets to predict essential proteins. However, a comprehensive web platform that facilitates the analysis and prediction of essential proteins is missing. In this study, we design, implement, and release NetEPD: a network-based essential protein discovery platform. This resource integrates data on Protein-Protein Interaction (PPI) networks, gene expression, subcellular localization, and a native set of essential proteins. It also computes a variety of node centrality measures, evaluates the predictions of essential proteins, and visualizes PPI networks. This comprehensive platform functions by implementing four activities, which include the collection of datasets, computation of centrality measures, evaluation, and visualization. The results produced by NetEPD are visualized on its website, and sent to a user-provided email, and they are available to download in a parsable format. This platform is freely available at http://bioinformatics.csu.edu.cn/netepd.

Keywords: visualization, essential proteins, centrality, data integration, evaluation

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Received: 11 September 2019
Accepted: 16 September 2019
Published: 13 January 2020
Issue date: August 2020

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 61832019, 61622213, and 61728211) and the 111 Project (No. B18059).

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