SingPro 2.0: a proteomics-centric knowledge base for single-cell multimodal profiling.

Protein-inclusive single-cell multimodal profiling has emerged as a transformative strategy for resolving cellular heterogeneity by jointly measuring proteins and complementary molecular features in the same cells. The resulting protein-inclusive datasets are increasingly used to characterize cellular states, construct multimodal cell atlases, and decode disease mechanisms. However, such data are rarely included in existing databases. In this study, SingPro was updated from a single-cell proteomics database into a proteomics-centric knowledge base for single-cell multimodal profiling. Distinct from existing resources, the updated SingPro (a) systematically curates data and experimental details from 814 protein-inclusive multimodal studies encompassing ~81.5 million cells across 29 tissues, 44 diseases, and multiple species; (b) covers 5 omics modalities through 12 experimental technologies that simultaneously profile proteins with messenger RNA, chromatin accessibility, or other measurements in the same cell; and (c) provides cross-modality visualization for joint analysis. SingPro is freely accessible without requiring login or registration at: https://idrblab.org/singpro/.

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Publication Details

Journal
PubMed
Published
2026-09-30
DOI
https://doi.org/10.1093/nar/gkag933
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

SingPro 2.0: a proteomics-centric knowledge base for single-cell multimodal profiling.

Minjie Mou, Xichen Lian, Huaicheng Sun, Jiannan Deng et al.
PubMed
Single-cell and spatial transcriptomics
article

SingPro 2.0: a proteomics-centric knowledge base for single-cell multimodal profiling.

Minjie Mou, Xichen Lian, Huaicheng Sun, Jiannan Deng, Ziqi Pan, Yijun Jiang, Yuan Zhou, Zijie Zhu, Yuting Kou, Yintao Zhang, Feng Zhu, Xiuna Sun, Qingxia Yang
article en

Abstract

Protein-inclusive single-cell multimodal profiling has emerged as a transformative strategy for resolving cellular heterogeneity by jointly measuring proteins and complementary molecular features in the same cells. The resulting protein-inclusive datasets are increasingly used to characterize cellular states, construct multimodal cell atlases, and decode disease mechanisms. However, such data are rarely included in existing databases. In this study, SingPro was updated from a single-cell proteomics database into a proteomics-centric knowledge base for single-cell multimodal profiling. Distinct from existing resources, the updated SingPro (a) systematically curates data and experimental details from 814 protein-inclusive multimodal studies encompassing ~81.5 million cells across 29 tissues, 44 diseases, and multiple species; (b) covers 5 omics modalities through 12 experimental technologies that simultaneously profile proteins with messenger RNA, chromatin accessibility, or other measurements in the same cell; and (c) provides cross-modality visualization for joint analysis. SingPro is freely accessible without requiring login or registration at: https://idrblab.org/singpro/.

PubMed
Sir Run Run Shaw Hospital (CN), Women's Hospital, School of Medicine, Zhejiang University (CN), Second Affiliated Hospital of Zhejiang University (CN), Zhejiang University (CN)
Openalex Percentile: Top 20%
Single-cell and spatial transcriptomics
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SingPro 2.0: a proteomics-centric knowledge base for single-cell multimodal profiling. — Minjie Mou, Xichen Lian, et al. · PubMed (2026) | TGRS Research Map | TGRS