Improving miRNA Target Prediction Using CLASH Data

4Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Li, X., & Hu, H. (2019). Improving miRNA Target Prediction Using CLASH Data. In Methods in Molecular Biology (Vol. 1970, pp. 75–83). Humana Press Inc. https://doi.org/10.1007/978-1-4939-9207-2_6

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free