Evidence map›Paper›PMID 42742132›Full record

ArticleeLife2026

Comprehensive RNA velocity by modeling the cascade of gene regulation, transcription, and splicing from single-cell RNA sequencing data with TSvelo.

Jiachen Li, Zhe Wang, Hong-Bin Shen, Ye Yuan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in eLife, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Jiachen LiState Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0000-0001-9137-6262
Zhe WangState Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, China.
Hong-Bin ShenInstitute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China.
Ye YuanState Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0009-0003-7969-469X

Funding

National Key Research and Development Program of China 2023YFF1204500National Natural Science Foundation of China 62503452
6 · The paper itself

Abstract

RNA velocity approaches fit gene dynamics and infer cell fate by modeling the splicing process using single-cell RNA sequencing (scRNA-seq) data. However, due to the short time scale of splicing, high noise, and large complexity of data, existing RNA velocity methods often fail to precisely capture the complex velocity dynamics for individual genes and single cells, which makes their downstream analysis less reliable and less robust. We propose

Indexed as

Gene Expression RegulationRNARNA SplicingSequence Analysis, RNASingle-Cell AnalysisTranscription, GeneticAnimalsMiceSingle-Cell Gene Expression AnalysisRNAcell trajectorycomputational biologymouseRNA velocityscRNA-seq analysissystems biology

Identifiers

PMID42742132
PMCPMC13577664

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.