Evidence map›Paper›PMID 39738650›Full record

ArticleScientific reports2024

MTFAP: a comprehensive platform for predicting and analyzing master transcription factors.

Jianyuan Zhou, Haojie Yu, Chunhui Lou, Min Yang, Yanshang Li, Qian Yang, Shuhan Li, Chunwang Ji, Song Li, Shuang Wang and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Jianyuan ZhouDepartment of Medical Oncology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.
Haojie YuSchool of Medical Informatics, Harbin Medical University, Daqing Campus, Daqing, 163319, China.
Chunhui LouSchool of Medical Informatics, Harbin Medical University, Daqing Campus, Daqing, 163319, China.
Min YangDepartment of Biochemistry and Molecular Biology, Medical College of Shantou University, Shantou, China.
Yanshang LiDepartment of Biochemistry and Molecular Biology, Medical College of Shantou University, Shantou, China.
Qian YangDepartment of Medical Oncology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.
Shuhan LiDepartment of Medical Oncology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.
Chunwang JiDepartment of Medical Oncology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.
Song LiDepartment of Medical Oncology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.
Shuang WangDepartment of Medical Oncology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China.
Haotian CaoDepartment of Oral & Maxillofacial Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China. caobleat@hotmail.com.
Xuecang LiSchool of Medical Informatics, Harbin Medical University, Daqing Campus, Daqing, 163319, China. eazier@qq.com.
Lian LiuDepartment of Medical Oncology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250012, Shandong, China. lianliu@sdu.edu.cn.

Funding

Youth Project of Guangdong Basic and Applied Basic Research Foundation 2021A1515110828
6 · The paper itself

Abstract

Master transcription factors (MTFs) activate gene expression in pluripotent embryonic stem cells (ESCs) by binding to enhancers and super-enhancers, which precisely control ESC fate. Compelling evidence reveals a strong correlation between the operation of MTFs and the initiation and progression of cancer. Nevertheless, the challenge of identifying MTFs imposes a barrier for researchers. Therefore, we developed a master transcription factors prediction and analysis web resource (MTFAP). MTFAP is a comprehensive web tool designed to predict and analyze MTFs with different data types. To enhance user experience and facilitate exploration of interest MTFs, MTFAP offers search and browse functionalities. Furthermore, we have developed a Docker file to empower users with the capability to conduct localized analyses Additionally, MTFAP extends support for further analysis and data visualization for the MTFs identified by Coltron and CRCmapper. The platform is freely available at http://www.xiejjlab.bio/MTFAP/.

Indexed as

Transcription FactorsAnimalsComputational BiologyEmbryonic Stem CellsHumansInternetPluripotent Stem CellsSoftwareTranscription FactorsBulk RNA-seqCore regulatory circuitMaster transcription factorsSingle-cell RNA-seq

Identifiers

PMID39738650
PMCPMC11685651

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.