ArticlePLoS computational biology2019
PRAS: Predicting functional targets of RNA binding proteins based on CLIP-seq peaks.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 10 citations in OpenAlex.
- RNA binding proteins (RBPs) on genetic stability and diseases.Global medical genetics · 2025Review
- Integrative genome-wide analysis reveals EIF3A as a key downstream regulator of translational repressor protein Musashi 2 (MSI2).NAR cancer · 2022Article
- The landscape of alternative polyadenylation in single cells of the developing mouse embryo.Nature communications · 2021Article
- Large-scale analysis of the position-dependent binding and regulation of human RNA binding proteins.Quantitative biology (Beijing, China) · 2020Article
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Authors and funding
4 authors at 2 institutions in 1 country.
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Abstract
RNA-protein interaction plays important roles in post-transcriptional regulation. Recent advancements in cross-linking and immunoprecipitation followed by sequencing (CLIP-seq) technologies make it possible to detect the binding peaks of a given RNA binding protein (RBP) at transcriptome scale. However, it is still challenging to predict the functional consequences of RBP binding peaks. In this study, we propose the Protein-RNA Association Strength (PRAS), which integrates the intensities and positions of the binding peaks of RBPs for functional mRNA targets prediction. We illustrate the superiority of PRAS over existing approaches on predicting the functional targets of two related but divergent CELF (CUGBP, ELAV-like factor) RBPs in mouse brain and muscle. We also demonstrate the potential of PRAS for wide adoption by applying it to the enhanced CLIP-seq (eCLIP) datasets of 37 RNA decay related RBPs in two human cell lines. PRAS can be utilized to investigate any RBPs with available CLIP-seq peaks. PRAS is freely available at http://ouyanglab.jax.org/pras/.
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