Evidence map›Paper›PMID 40323145›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

MRAS: Master Regulator Analysis of Alternative Splicing.

Lei Zhou, Yue Huang, Yang Zhao, Dan Guo, Xiao Wen, Ruihong Xu, Xuan Lv, Song Wu, Sicheng Jing, Zhaoqi Liu

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. MRAS: Master Regulator Analysis of Alternative Splicing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    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

10 authors.

Lei ZhouChina National Center for Bioinformation, Beijing, 100101, China.
Yue HuangChina National Center for Bioinformation, Beijing, 100101, China.
Yang ZhaoChina National Center for Bioinformation, Beijing, 100101, China.
Dan GuoChina National Center for Bioinformation, Beijing, 100101, China.
Xiao WenChina National Center for Bioinformation, Beijing, 100101, China.
Ruihong XuChina National Center for Bioinformation, Beijing, 100101, China.
Xuan LvChina National Center for Bioinformation, Beijing, 100101, China.
Song WuBeijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.
Sicheng JingDepartment of Biology, University of California San Diego, San Diego, CA, 92122, USA.
Zhaoqi LiuChina National Center for Bioinformation, Beijing, 100101, China.ORCID https://orcid.org/0000-0002-3798-9583

Funding

National Key R&D Program of China 2022YFC2704202National Key R&D Program of China 2023YFF0725400National Natural Science Foundation of China 32170565
6 · The paper itself

Abstract

As a molecular feature that characterizes most tumor types, cancer-associated splicing dysregulation largely arises from recurrent genetic mutations and altered expression of trans-acting splicing factors. Although splicing factor mutations occur less frequently in solid tumors, splicing disorders are pervasive and proven to promote tumorigenesis. However, it still lacks an efficient way to identify the key splicing factors at the top regulatory hierarchy whose abnormal expressions induce such splicing disorders and drive phenotypic variability. Here, MRAS (Master Regulator analysis of Alternative Splicing) is introduced, a computational method designed to pinpoint the pivotal splicing factors that play a central role in shaping splicing regulatory networks and influencing cellular processes. MRAS is demonstrated its power by identifying master splicing regulators associated with various disease phenotypes, including tumor initiation, progression, metastasis, and treatment resistance. Moreover, by applying MRAS to single-cell RNA-seq data, crucial regulatory relationships that govern cell-type specific splicing programs have been uncovered. Overall, MRAS presented as an accurate and versatile approach to unraveling the underlying mechanism of splicing regulation.

Indexed as

Alternative SplicingComputational BiologyNeoplasmsRNA Splicing FactorsHumansRNA Splicing Factorsalternative splicingmaster regulator analysisRNA binding proteinsplicing regulatory network

Identifiers

PMID40323145
PMCPMC12140307

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.