Evidence map›Paper›PMID 37730114›Full record

ArticleGenomics, proteomics & bioinformatics2023

HPC-Atlas: Computationally Constructing A Comprehensive Atlas of Human Protein Complexes.

Yuliang Pan, Ruiyi Li, Wengen Li, Liuzhenghao Lv, Jihong Guan, Shuigeng Zhou

Abstract read
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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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

6 authors.

Yuliang PanDepartment of Computer Science and Technology, College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China.
Ruiyi LiTranslational Medical Center for Stem Cell Therapy, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200120, China.
Wengen LiDepartment of Computer Science and Technology, College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China.
Liuzhenghao LvDepartment of Computer Science and Technology, College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China.
Jihong GuanDepartment of Computer Science and Technology, College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China. Electronic address: jhguan@tongji.edu.cn.
Shuigeng ZhouShanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai 200433, China. Electronic address: sgzhou@fudan.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A fundamental principle of biology is that proteins tend to form complexes to play important roles in the core functions of cells. For a complete understanding of human cellular functions, it is crucial to have a comprehensive atlas of human protein complexes. Unfortunately, we still lack such a comprehensive atlas of experimentally validated protein complexes, which prevents us from gaining a complete understanding of the compositions and functions of human protein complexes, as well as the underlying biological mechanisms. To fill this gap, we built Human Protein Complexes Atlas (HPC-Atlas), as far as we know, the most accurate and comprehensive atlas of human protein complexes available to date. We integrated two latest protein interaction networks, and developed a novel computational method to identify nearly 9000 protein complexes, including many previously uncharacterized complexes. Compared with the existing methods, our method achieved outstanding performance on both testing and independent datasets. Furthermore, with HPC-Atlas we identified 751 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-affected human protein complexes, and 456 multifunctional proteins that contain many potential moonlighting proteins. These results suggest that HPC-Atlas can serve as not only a computing framework to effectively identify biologically meaningful protein complexes by integrating multiple protein data sources, but also a valuable resource for exploring new biological findings. The HPC-Atlas webserver is freely available at http://www.yulpan.top/HPC-Atlas.

Indexed as

Computational BiologyProtein Interaction MappingAlgorithmsHumansProtein Interaction MapsProteinsSaccharomyces cerevisiaeProteinsComplex identification methodHuman protein complexMultifunctional proteinProtein interaction networkSARS-CoV-2-affected complex

Identifiers

PMID37730114
PMCPMC10928439

What OpenQuestion holds

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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.