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Improving miRNA Target Prediction Using CLASH Data

  • Xiaoman Li
  • Haiyan HuEmail author
Protocol
Part of the Methods in Molecular Biology book series (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.

Key words

miRNA CLASH data miRNA target prediction New features TarPmiR 

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Burnett School of Biomedical Science, College of MedicineUniversity of Central FloridaOrlandoUSA
  2. 2.Department of Computer ScienceUniversity of Central FloridaOrlandoUSA

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