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PBMarsNet: A Multivariate Adaptive Regression Splines Based Method to Reconstruct Gene Regulatory Networks

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Bioinformatics Research and Applications (ISBRA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10847))

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Abstract

Gene Regulatory Network (GRN) is a directed graph which describes the regulations between genes. The problem of reconstructing GRNs has been studied for decades. Most of existing methods infer the GRNs from gene expression data. Previous studies use random forest, partial least squares or other feature selection techniques to solve it. In this paper, we propose a Multivariate Adaptive Regression Splines (MARS) based method to estimate the feature importance and reconstruct the GRNs. MARS can catch the nonlinear relationships between genes. To avoid the overfitting and make the estimation robust, we apply an ensemble model of MARS based on bootstrap and weighted features by PMI (Part mutual information), called PBMarsNet. The results show that PBMarsNet performs better than the state-of-the-art methods.

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Fund Sponsored

This work was supported in part by the National Natural Science Foundation of China No. 61622213, No. 61732009, No. 61772552 and No. 61728211.

Author information

Authors and Affiliations

  1. School of Information Science and Engineering, Central South University, Changsha, 410083, China

    Siyu Zhao, Ruiqing Zheng, Xiang Chen & Min Li

  2. Department of Mechanical Engineering and Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada

    Fang-Xiang Wu

  3. Department of Computer Science, Old Dominion University, Norfolk, VA, USA

    Yaohang Li

Authors
  1. Siyu Zhao
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  2. Ruiqing Zheng
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  3. Xiang Chen
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  4. Yaohang Li
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  5. Fang-Xiang Wu
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  6. Min Li
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Corresponding author

Correspondence to Min Li .

Editor information

Editors and Affiliations

  1. Chinese Academy of Sciences, Beijing, China

    Fa Zhang

  2. Georgia State University, Atlanta, GA, USA

    Zhipeng Cai

  3. Georgia State University, Atlanta, GA, USA

    Pavel Skums

  4. Chinese Academy of Sciences, Beijing, China

    Shihua Zhang

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Zhao, S., Zheng, R., Chen, X., Li, Y., Wu, FX., Li, M. (2018). PBMarsNet: A Multivariate Adaptive Regression Splines Based Method to Reconstruct Gene Regulatory Networks. In: Zhang, F., Cai, Z., Skums, P., Zhang, S. (eds) Bioinformatics Research and Applications. ISBRA 2018. Lecture Notes in Computer Science(), vol 10847. Springer, Cham. https://doi.org/10.1007/978-3-319-94968-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-94968-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94967-3

  • Online ISBN: 978-3-319-94968-0

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