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Bootstrapped Integrative Hypothesis Test, COPD-Lung Cancer Differentiation, and Joint miRNAs Biomarkers

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Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques (IScIDE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9243))

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Abstract

Integrative Hypothesis Test (IHT) has been recently proposed for an integrated study of hypothesis test, classification analysis and feature selection. This paper not only applies IHT to identifying miRNAs biomarkers for the differentiation of lung cancer and Chronic Obstructive Pulmonary Disease (COPD), but also proposes a bootstrapping method to enhance the reliability of IHT ranking on samples with a small size and missing values. On the GEO data set GSE24709, the previously reported fourteen differentially expressed miRNAs have been re-confirmed via one by one enumeration of their IHT ranking, with two doubtful miRNAs identified. Moreover, every pair of miRNAs is also exhaustively enumerated to examine the pairwise effect via the p-value, misclassification, and correlation, further identifying those that take core roles in coordinated effects. Furthermore, linked cliques are found featured with joint differentiation performances, which motivates us to identify such clique patterns as joint miRNAs biomarkers.

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Acknowledgment

This work was partially supported by the National Natural Science Foundation of China (Grant No. 61272248), the National Basic Research Program of China (Grant No. 2013CB329401, the Science and Technology Commission of Shanghai Municipality (Grant No.13511500200), and Shanghai Jiao Tong University fund for Zhiyuan Chair Professorship.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai, 200240, China

    Kai-Ming Jiang, Bao-Liang Lu & Lei Xu

  2. The Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai, 200240, China

    Kai-Ming Jiang, Bao-Liang Lu & Lei Xu

  3. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, NT, Hong Kong, China

    Lei Xu

Authors
  1. Kai-Ming Jiang
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  2. Bao-Liang Lu
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  3. Lei Xu
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Corresponding author

Correspondence to Lei Xu .

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Editors and Affiliations

  1. Zhejiang University, Hangzhou, China

    Xiaofei He

  2. Xidian University, Xi'an, China

    Xinbo Gao

  3. Northwestern Polytechnical University, Xi'an, China

    Yanning Zhang

  4. Nanjing University, Nanjing, China

    Zhi-Hua Zhou

  5. Chinese Academy of Sciences, Beijing, China

    Zhi-Yong Liu

  6. Suzhou University of Science and Technology, Suzhou, China

    Baochuan Fu

  7. Suzhou University of Science and Technology, Jiangsu, China

    Fuyuan Hu

  8. Suzhou University of Science and Technology, Jiangsu, China

    Zhancheng Zhang

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Jiang, KM., Lu, BL., Xu, L. (2015). Bootstrapped Integrative Hypothesis Test, COPD-Lung Cancer Differentiation, and Joint miRNAs Biomarkers. In: He, X., et al. Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques. IScIDE 2015. Lecture Notes in Computer Science(), vol 9243. Springer, Cham. https://doi.org/10.1007/978-3-319-23862-3_53

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  • DOI: https://doi.org/10.1007/978-3-319-23862-3_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23861-6

  • Online ISBN: 978-3-319-23862-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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