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Cancer Bioinformatics pp 139–155Cite as

Computational Analysis of lncRNA Function in Cancer

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 1878))

Abstract

Long noncoding RNAs (lncRNAs) have been shown to play crucial roles in cancer biology. With the help of computational analysis illustrated here, the joint effects of lncRNAs and clinical variables can be quantified in a Cox model on cancer recurrence. Of importance, the predictive accuracy was then validated with the prognostic scores computed based on the suggested model. Further investigation of these potential lncRNAs would provide useful insights following the study of the mechanisms underlying the differential expression of these lncRNAs in association with and possibly contributing to cancer recurrence. Ultimately, the expanding knowledge of the function of lncRNAs curated by computational analysis will suggest new targets for cancer treatment.

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Authors and Affiliations

  1. Center of Clinical and Translational Sciences and Department of Internal Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA

    Xu Zhang

  2. Cancer Institute, Department of Radiation Oncology, University of Mississippi Medical Center, Jackson, MS, USA

    Tsui-Ting Ho

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  1. Xu Zhang
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Correspondence to Xu Zhang .

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Editors and Affiliations

  1. Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA

    Alexander Krasnitz

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Zhang, X., Ho, TT. (2019). Computational Analysis of lncRNA Function in Cancer. In: Krasnitz, A. (eds) Cancer Bioinformatics. Methods in Molecular Biology, vol 1878. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8868-6_8

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  • DOI: https://doi.org/10.1007/978-1-4939-8868-6_8

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  • Publisher Name: Humana Press, New York, NY

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