ArticleNature communications2026
RAISE quantifies RNA binding protein activity via transcriptomic profiling.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- RAISE quantifies RNA binding protein activity via transcriptomic profiling.Nature communications · 2026Article
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Authors and funding
7 authors.
Funding
Abstract
Alternative splicing (AS) greatly expands proteomic diversity and is tightly regulated by RNA-binding proteins (RBPs), whose activities reflect both the direction and the strength of their regulatory influence. However, inferring RBP activity remains challenging owing to the incomplete characterization of RBP-splicing regulatory relationships and the lack of experimental approaches for direct activity measurement. Here, we present RAISE, a computational framework that integrates multimodal evidence including CLIP-seq, sequence motifs, and splicing alterations derived from RNA-seq data to identify RBP targets, construct RBP-exon regulatory networks and quantitatively infer RBP activity across conditions. The targets identified by RAISE recapitulate the known functions and characteristic regulatory patterns of RBPs. RAISE accurately inferred the activity of diverse RBPs across multiple cell lines and perturbation experiments, and effectively captured activity changes independent of RBP expression levels. When applied to The Cancer Genome Atlas (TCGA) datasets, RAISE revealed RBPs with altered activity in cancer, underscoring its potential for large-scale analyses of splicing regulation. Furthermore, we provide RAISEDB, a database of predicted RBP-exon interactions. Collectively, RAISE enables systematic quantification of RBP activity and illuminates splicing regulatory networks across biological and disease contexts.
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