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iCLIP - Transcriptome-wide Mapping of Protein-RNA Interactions with Individual Nucleotide Resolution
Published on: April 30, 2011
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Bioinformatic tools for analysis of CLIP ribonucleoprotein data
1Laboratory of Genetics and Genomics, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
Wiley Interdisciplinary Reviews. RNA
|December 24, 2016
Summary
This review guides researchers in selecting computational tools for analyzing RNA-binding protein (RBP) interactions. It focuses on crosslinking and immunoprecipitation (CLIP) methods and available software for RBP-RNA analysis.
Area of Science:
- Molecular Biology
- Computational Biology
- Bioinformatics
Background:
- Understanding RNA-binding protein (RBP) and RNA interactions is crucial but complex.
- Advancements in molecular and computational techniques have led to numerous software tools for RBP-RNA analysis.
- Selecting appropriate software for specific RBP-RNA studies presents a challenge for researchers.
Purpose of the Study:
- To review state-of-the-art molecular biology techniques for studying RBP-RNA interactions.
- To focus on crosslinking and immunoprecipitation (CLIP) methods for mapping RBP-RNA interactions.
- To provide an overview of software tools and databases for analyzing common CLIP methods.
Main Methods:
- Review of molecular biology techniques, specifically crosslinking and immunoprecipitation (CLIP).
- Focus on widely used CLIP methods: HITS-CLIP, PAR-CLIP, and individual-nucleotide resolution CLIP (iCLIP).
- Survey of available computational software and databases for analyzing CLIP data.
Main Results:
- Identification and description of various software tools and databases for CLIP data analysis.
- Categorization of tools relevant to HITS-CLIP, PAR-CLIP, and iCLIP methodologies.
- Guidance for laboratories in choosing suitable bioinformatics tools for their RBP-RNA research.
Conclusions:
- The study provides a valuable resource for researchers navigating the complex landscape of RBP-RNA interaction analysis tools.
- Effective selection of computational tools is essential for advancing RNP biology research.
- This review aims to facilitate informed decisions in choosing software for CLIP data analysis.
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