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International Symposium on Bioinformatics Research and Applications

ISBRA 2019: Bioinformatics Research and Applications pp 127–137Cite as

Identifying Human Essential Genes by Network Embedding Protein-Protein Interaction Network

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 11490))

Abstract

Essential genes play an indispensable role in cell viability and fertility. Identifying human essential genes helps us to study the functions of human genes, but also provides a way for finding potential targets for cancer and other diseases. Recently, with the publishing of human essential gene data and the availability of a large amount of biological data, some computational methods have been proposed to predict human essential genes based on genes’ DNA sequence or their topological properties in the protein-protein interaction (PPI) network. However, there is still some room to improve the prediction accuracy. In this work, we propose a novel supervised method to predict human essential genes by network embedding protein-protein interaction network. Our method extracts the features of the genes in network by mapping them to a latent space of features that maximally preserves the relationships between the genes and their network neighborhoods. After that, the features are input into a SVM classifier to predict human essential genes. Two human PPI networks are employed to evaluate the effectiveness of our method. The prediction results show that our method outperforms the method that only uses genes’ sequence information, but also is obviously superior to the method utilizing genes’ centrality properties in the network as input features.

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Acknowledgment

This work is supported in part by the National Natural Science Foundation of China under grant No. 31560317, No. 61502214, No. 61472133, No. 61502166, No. 61702122 and No. 81560221. Natural Science Foundation of Yunnan Province of China (No. 2016FB107).

Author information

Authors and Affiliations

  1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650050, China

    Wei Dai, Qi Chang & Wei Peng

  2. Computer Technology Application Key Lab of Yunnan Province, Kunming University of Science and Technology, Kunming, 650050, China

    Wei Peng & Yongjiang Li

  3. College of Engineering and Design, Hunan Normal University, Changsha, 410081, China

    Jiancheng Zhong

Authors
  1. Wei Dai
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  2. Qi Chang
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  3. Wei Peng
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  4. Jiancheng Zhong
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  5. Yongjiang Li
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Corresponding author

Correspondence to Wei Peng .

Editor information

Editors and Affiliations

  1. Georgia State University, Atlanta, GA, USA

    Zhipeng Cai

  2. Georgia State University, Atlanta, GA, USA

    Pavel Skums

  3. Central South University, Changsha, China

    Min Li

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Dai, W., Chang, Q., Peng, W., Zhong, J., Li, Y. (2019). Identifying Human Essential Genes by Network Embedding Protein-Protein Interaction Network. In: Cai, Z., Skums, P., Li, M. (eds) Bioinformatics Research and Applications. ISBRA 2019. Lecture Notes in Computer Science(), vol 11490. Springer, Cham. https://doi.org/10.1007/978-3-030-20242-2_11

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  • DOI: https://doi.org/10.1007/978-3-030-20242-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20241-5

  • Online ISBN: 978-3-030-20242-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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