Evidence map›Paper›PMID 37819028›Full record

ArticleNucleic acids research2024

SingPro: a knowledge base providing single-cell proteomic data.

Xichen Lian, Yintao Zhang, Ying Zhou, Xiuna Sun, Shijie Huang, Haibin Dai, Lianyi Han, Feng Zhu

Abstract read
In one paragraph

Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Review
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  4. Review
  5. Article
  6. Review
  7. Mass Spectrometry-based Solutions for Single-cell Proteomics.Genomics, proteomics & bioinformatics · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. 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

8 authors.

Xichen LianCollege of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
Yintao ZhangCollege of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
Ying ZhouCollege of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
Xiuna SunCollege of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
Shijie HuangCollege of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
Haibin DaiCollege of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.
Lianyi HanGreater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences, Fudan University, Shanghai 315211, China.ORCID 0000-0002-6364-7843
Feng ZhuCollege of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China.ORCID 0000-0001-6661-0002

Funding

Alibaba CloudAlibaba-Zhejiang University Joint Research Center of Future Digital HealthcareFundamental Research Funds for Central Universities 2018QNA7023Information Technology Center of Zhejiang UniversityKey R&D Program of Zhejiang Province 2020C03010National Key R&D Program of China 2022YFC3400501National Natural Science Foundation of China 82373790Natural Science Foundation of Zhejiang Province LR21H300001'Ten Thousand Plan' National High-Level Talents Special Support Plan of ChinaThe Double Top-Class Universities 181201*194232101Westlake Laboratory
6 · The paper itself

Abstract

Single-cell proteomics (SCP) has emerged as a powerful tool for detecting cellular heterogeneity, offering unprecedented insights into biological mechanisms that are masked in bulk cell populations. With the rapid advancements in AI-based time trajectory analysis and cell subpopulation identification, there exists a pressing need for a database that not only provides SCP raw data but also explicitly describes experimental details and protein expression profiles. However, no such database has been available yet. In this study, a database, entitled 'SingPro', specializing in single-cell proteomics was thus developed. It was unique in (a) systematically providing the SCP raw data for both mass spectrometry-based and flow cytometry-based studies and (b) explicitly describing experimental detail for SCP study and expression profile of any studied protein. Anticipating a robust interest from the research community, this database is poised to become an invaluable repository for OMICs-based biomedical studies. Access to SingPro is unrestricted and does not mandate a login at: http://idrblab.org/singpro/.

Indexed as

Databases, ProteinProtein Processing, Post-TranslationalProteomicsKnowledge BasesMass SpectrometrySingle-Cell Analysis

Identifiers

PMID37819028
PMCPMC10767818

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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.