SingPro: a knowledge base providing single-cell proteomic data

Author:

Lian Xichen123,Zhang Yintao1,Zhou Ying14,Sun Xiuna1,Huang Shijie1,Dai Haibin1,Han Lianyi2ORCID,Zhu Feng13ORCID

Affiliation:

1. College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University , Hangzhou 310058, China

2. Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences, Fudan University , Shanghai 315211, China

3. Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare , Hangzhou 330110, China

4. State Key Laboratory for Diagnosis and Treatment of Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang Provincial Key Laboratory for Drug Clinical Research and Evaluation, The First Affiliated Hospital, Zhejiang University , Hangzhou 310000, China

Abstract

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/.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

National Key R&D Program of China

‘Ten Thousand Plan’ National High-Level Talents Special Support Plan of China

The Double Top-Class Universities

Fundamental Research Funds for Central Universities

Key R&D Program of Zhejiang Province

Westlake Laboratory

Alibaba Cloud

Information Technology Center of Zhejiang University

Alibaba-Zhejiang University Joint Research Center of Future Digital Healthcare

Publisher

Oxford University Press (OUP)

Subject

Genetics

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