Evidence map›Paper›PMID 42864337›Full record

ArticleNature communications2026

RAISE quantifies RNA binding protein activity via transcriptomic profiling.

Yilei Liu, Yingtung Lo, Youqi Zheng, Pinxin Xiong, Jianzhong Lu, Zhixing Feng, Huijuan Feng

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yilei LiuState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences, Center for Integrative Spatial-Omics Research, Fudan University, Shanghai, China.ORCID http://orcid.org/0009-0002-7085-2471
Yingtung LoSchool of Pharmaceutical Sciences, Fudan University, Laboratory of Smart Drug Delivery, MOE, State Key Laboratory of Advanced Drug Formulations for Overcoming Delivery Barriers, Shanghai, China.
Youqi ZhengState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences, Center for Integrative Spatial-Omics Research, Fudan University, Shanghai, China.ORCID http://orcid.org/0009-0001-1947-9344
Pinxin XiongState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences, Center for Integrative Spatial-Omics Research, Fudan University, Shanghai, China.ORCID http://orcid.org/0009-0003-2227-8986
Jianzhong LuSchool of Pharmaceutical Sciences, Fudan University, Laboratory of Smart Drug Delivery, MOE, State Key Laboratory of Advanced Drug Formulations for Overcoming Delivery Barriers, Shanghai, China. jzlu@shmu.edu.cn.
Zhixing FengDepartment of Clinical Genetics, Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China. fengzhixing@shsmu.edu.cn.ORCID http://orcid.org/0000-0003-0308-8549
Huijuan FengState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Life Sciences, Center for Integrative Spatial-Omics Research, Fudan University, Shanghai, China. huijuanfeng@fudan.edu.cn.ORCID http://orcid.org/0000-0002-4005-560X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32370695National Natural Science Foundation of China (National Science Foundation of China) 32470684
6 · The paper itself

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.

Indexed as

Gene Expression ProfilingRNA-Binding ProteinsTranscriptomeAlternative SplicingComputational BiologyExonsGene Regulatory NetworksHumansNeoplasmsRNA-Binding Proteins

Identifiers

PMID42864337
PMCPMC13658764

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.