Evidence map›Paper›PMID 39436241›Full record

ArticleGenomics, proteomics & bioinformatics2025

EryDB: A Transcriptomic Profile Database for Erythropoiesis and Erythroid-related Diseases.

Guangmin Zheng, Song Wu, Zhaojun Zhang, Zijuan Xin, Lijuan Zhang, Siqi Zhao, Jing Wu, Yanxia Liu, Meng Li, Xiuyan Ruan and 4 more

Abstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2025. 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. Review
  2. Biomedical Big Data and Artificial Intelligence in Blood.Genomics, proteomics & bioinformatics · 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

14 authors.

Guangmin ZhengChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0002-3781-170X
Song WuChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0002-0923-639X
Zhaojun ZhangChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0003-0490-6507
Zijuan XinChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0001-9418-4848
Lijuan ZhangChina National Center for Bioinformation, Beijing 100101, China.ORCID 0009-0009-4246-929X
Siqi ZhaoChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0003-2341-4989
Jing WuChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0001-6032-0979
Yanxia LiuChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0002-0608-2217
Meng LiChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0003-0369-5867
Xiuyan RuanChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0002-2181-1529
Nan QiaoHuawei Cloud Computing Technologies Co., Ltd., Guiyang 550029, China.ORCID 0000-0002-2740-262X
Yiming BaoChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0002-9922-9723
Hongzhu QuChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0001-7013-8409
Xiangdong FangChina National Center for Bioinformation, Beijing 100101, China.ORCID 0000-0002-6628-8620

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Erythropoiesis is a finely regulated and complex process that involves multiple transformations from hematopoietic stem cells to mature red blood cells at hematopoietic sites from the embryonic to adult stages. Investigations into its molecular mechanisms have generated a wealth of expression data, including bulk and single-cell RNA sequencing data. A comprehensively integrated and well-curated erythropoiesis-specific database will greatly facilitate the mining of gene expression data and enable large-scale research of erythropoiesis and erythroid-related diseases. Here, we present EryDB, an open-access and comprehensive database dedicated to the collection, integration, analysis, and visualization of transcriptomic data for erythropoiesis and erythroid-related diseases. Currently, the database includes expertly curated quality-assured data of 3803 samples and 1,187,119 single cells derived from 107 public studies of three species (Homo sapiens, Mus musculus, and Danio rerio), nine tissue types, and five diseases. EryDB provides users with the ability to not only browse the molecular features of erythropoiesis between tissues and species, but also perform computational analyses of single-cell and bulk RNA sequencing data, thus serving as a convenient platform for customized queries and analyses. EryDB v1.0 is freely accessible at https://ngdc.cncb.ac.cn/EryDB/home.

Indexed as

Databases, GeneticErythropoiesisTranscriptomeAnimalsGene Expression ProfilingHumansMiceZebrafishDatabaseData integrationErythropoiesisscRNA-seqTranscriptome

Identifiers

PMID39436241
PMCPMC13223742

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.