Literature DB >> 28008714

Bioinformatic tools for analysis of CLIP ribonucleoprotein data.

Supriyo De1, Myriam Gorospe1.   

Abstract

Investigating the interactions of RNA-binding proteins (RBPs) with RNAs is a complex task for molecular and computational biologists. The molecular biology techniques and the computational approaches to understand RBP-RNA (or ribonucleoprotein, RNP) interactions have advanced considerably over the past few years and numerous and diverse software tools have been developed to analyze these data. Accordingly, laboratories interested in RNP biology face the challenge of choosing adequately among the available software tools those that best address the biological problem they are studying. Here, we focus on state-of-the-art molecular biology techniques that employ crosslinking and immunoprecipitation (CLIP) of an RBP to study and map RNP interactions. We review the different software tools and databases available to analyze the most widely used CLIP methods, HITS-CLIP, PAR-CLIP, and iCLIP. WIREs RNA 2017, 8:e1404. doi: 10.1002/wrna.1404 For further resources related to this article, please visit the WIREs website. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

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Year:  2016        PMID: 28008714      PMCID: PMC5509467          DOI: 10.1002/wrna.1404

Source DB:  PubMed          Journal:  Wiley Interdiscip Rev RNA        ISSN: 1757-7004            Impact factor:   9.957


  83 in total

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Journal:  Bioinformatics       Date:  2015-09-05       Impact factor: 6.937

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Journal:  Bioinformatics       Date:  2012-09-28       Impact factor: 6.937

5.  Evidence-ranked motif identification.

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Journal:  Genome Biol       Date:  2010-02-15       Impact factor: 13.583

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7.  A model-based approach to identify binding sites in CLIP-Seq data.

Authors:  Tao Wang; Beibei Chen; MinSoo Kim; Yang Xie; Guanghua Xiao
Journal:  PLoS One       Date:  2014-04-08       Impact factor: 3.240

8.  dCLIP: a computational approach for comparative CLIP-seq analyses.

Authors:  Tao Wang; Yang Xie; Guanghua Xiao
Journal:  Genome Biol       Date:  2014-01-07       Impact factor: 13.583

9.  starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data.

Authors:  Jun-Hao Li; Shun Liu; Hui Zhou; Liang-Hu Qu; Jian-Hua Yang
Journal:  Nucleic Acids Res       Date:  2013-12-01       Impact factor: 16.971

10.  MicroRNA target site identification by integrating sequence and binding information.

Authors:  William H Majoros; Parawee Lekprasert; Neelanjan Mukherjee; Rebecca L Skalsky; David L Corcoran; Bryan R Cullen; Uwe Ohler
Journal:  Nat Methods       Date:  2013-05-26       Impact factor: 28.547

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  3 in total

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2.  RBP-Maps enables robust generation of splicing regulatory maps.

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Journal:  RNA       Date:  2018-11-09       Impact factor: 4.942

Review 3.  Next-generation sequencing: A new avenue to understand viral RNA-protein interactions.

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Journal:  J Biol Chem       Date:  2022-04-09       Impact factor: 5.486

  3 in total

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