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Improving miRNA Target Prediction Using CLASH Data

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Book cover MicroRNA Target Identification

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1970))

Abstract

In this chapter, we present a computational method, TarPmiR, for miRNA target prediction. TarPmiR is based on emerging features of miRNA–target interactions learned from CLASH (crosslinking, ligation and sequencing of hybrids) data. First, we introduce miRNA target prediction, delineate existing methods for miRNA target prediction, and discuss their usage and limitations. Next, we describe available CLASH data, the learning of new miRNA binding features from CLASH data, and the usage of CLASH features in miRNA target prediction. Finally, we detail the computational pipeline of TarPmiR, discuss its performance compared with existing computational methods for miRNA target prediction, and present its installation and usage for miRNA target prediction. This chapter will facilitate the common understanding of CLASH data, new characteristics of miRNA–target interactions, and the use of the CLASH based miRNA target prediction tool TarPmiR.

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Author information

Authors and Affiliations

  1. Burnett School of Biomedical Science, College of Medicine, University of Central Florida, Orlando, FL, USA

    Xiaoman Li

  2. Department of Computer Science, University of Central Florida, Orlando, FL, USA

    Haiyan Hu

Authors
  1. Xiaoman Li
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  2. Haiyan Hu
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Corresponding author

Correspondence to Haiyan Hu .

Editor information

Editors and Affiliations

  1. Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, NY, USA

    Alessandro Laganà

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Li, X., Hu, H. (2019). Improving miRNA Target Prediction Using CLASH Data. In: Laganà, A. (eds) MicroRNA Target Identification. Methods in Molecular Biology, vol 1970. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9207-2_6

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  • DOI: https://doi.org/10.1007/978-1-4939-9207-2_6

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-9206-5

  • Online ISBN: 978-1-4939-9207-2

  • eBook Packages: Springer Protocols

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