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International Conference on Intelligent Computing

ICIC 2018: Intelligent Computing Theories and Application pp 289–300Cite as

Combining mRNA, microRNA, Protein Expression Data and Driver Genes Information for Identifying Cancer-Related MicroRNAs

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10955))

Abstract

As is well-known, microRNAs (miRNAs), a short nor-coding RNA, play a vital role in important biological processes such as gene expression and transcriptional regulation. And it was reported that miRNAs have involved in the occurrence and development of various human cancer, which shows the potentiality of miRNAs in cancer treatment and diagnosis. However, it is a great challenge for the detection and prioritization of cancer-related miRNAs. In this paper, we proposed a novel approach which combines mRNA, miRNA, protein expression data by introducing dirver genes for identifying glioblastoma (GBM)-related miRNAs. And identified miRNAs were ranked by related scores. The performance of our method was evaluated by the proportion of the previously known miRNAs and the area under the receiver operating characteristic curves (AUC). A literature survey was also used to validate the detected results. A miRNA-gene regulatory module was constructed for understanding the biological function of ranked miRNAs in cancer.

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Acknowledgement

This work was supported by the grants of the National Science Foundation of China (Grant Nos. 61472467, 61672011, and 61471169) and the Collaboration and Innovation Center for Digital Chinese Medicine of 2011 Project of Colleges and Universities in Hunan Province.

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Authors and Affiliations

  1. College of Computer Science and Electronics Engineering, Hunan University, Changsha, 410082, Hunan, China

    Jiawei Lei & Shu-Lin Wang

  2. Biometric Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, 20850, USA

    Jianwen Fang

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  1. Jiawei Lei
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Correspondence to Shu-Lin Wang .

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Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

  3. Wuhan University of Science and Technology, Wuhan City, China

    Xiao-Long Zhang

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Lei, J., Wang, SL., Fang, J. (2018). Combining mRNA, microRNA, Protein Expression Data and Driver Genes Information for Identifying Cancer-Related MicroRNAs. In: Huang, DS., Jo, KH., Zhang, XL. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science(), vol 10955. Springer, Cham. https://doi.org/10.1007/978-3-319-95933-7_36

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  • DOI: https://doi.org/10.1007/978-3-319-95933-7_36

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-95933-7

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