Evidence map›Paper›PMID 32209698›Full record

ArticleScience signaling2020

An atlas of human metabolism.

Jonathan L Robinson, Pınar Kocabaş, Hao Wang, Pierre-Etienne Cholley, Daniel Cook, Avlant Nilsson, Mihail Anton, Raphael Ferreira, Iván Domenzain, Virinchi Billa and 10 more

Abstract read
In one paragraph

Article in Science signaling, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 246 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
246citing papers in PubMed, 2 pooled it
–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

246 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  12. EHMN2026Metabolites · 2026
    Article
  13. Review
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186 more citing papers are in PubMed but not listed here.

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

20 authors.

Jonathan L RobinsonDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0001-8567-5960
Pınar KocabaşDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0001-9788-2019
Hao WangDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0001-7475-0136
Pierre-Etienne CholleyDepartment of Biology and Biological Engineering, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.
Daniel CookDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0001-5534-8600
Avlant NilssonDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0002-9476-4516
Mihail AntonDepartment of Biology and Biological Engineering, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0002-7753-9042
Raphael FerreiraDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0001-9881-6232
Iván DomenzainDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0002-5322-2040
Virinchi BillaDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.
Angelo LimetaDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.
Alex HedinDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0002-0829-2496
Johan GustafssonDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0001-5072-2659
Eduard J KerkhovenDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0002-3593-5792
L Thomas SvenssonDepartment of Biology and Biological Engineering, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.ORCID 0000-0002-9190-2979
Bernhard O PalssonNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark.ORCID 0000-0003-2357-6785
Adil MardinogluDepartment of Protein Science, Science for Life Laboratory, KTH-Royal Institute of Technology, SE-10044 Stockholm, Sweden.ORCID 0000-0002-4254-6090
Lena HanssonDepartment of Biology and Biological Engineering, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden.
Mathias UhlénNovo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark.ORCID 0000-0002-4858-8056
Jens NielsenDepartment of Biology and Biological Engineering, Chalmers University of Technology, Kemivägen 10, SE-41258 Gothenburg, Sweden. nielsenj@chalmers.se.ORCID 0000-0002-9955-6003

Funding

Deciphering the coupled roles of protein secretion and metabolism in cancer using an integrative omics approachF32CA220848 · NCI · CHALMERS UNIVERSITY OF TECHNOLOGY · PI ROBINSON, JONATHAN · 2017 to 2019
$112k
NCI NIH HHS F32 CA220848
6 · The paper itself

Abstract

Genome-scale metabolic models (GEMs) are valuable tools to study metabolism and provide a scaffold for the integrative analysis of omics data. Researchers have developed increasingly comprehensive human GEMs, but the disconnect among different model sources and versions impedes further progress. We therefore integrated and extensively curated the most recent human metabolic models to construct a consensus GEM, Human1. We demonstrated the versatility of Human1 through the generation and analysis of cell- and tissue-specific models using transcriptomic, proteomic, and kinetic data. We also present an accompanying web portal, Metabolic Atlas (https://www.metabolicatlas.org/), which facilitates further exploration and visualization of Human1 content. Human1 was created using a version-controlled, open-source model development framework to enable community-driven curation and refinement. This framework allows Human1 to be an evolving shared resource for future studies of human health and disease.

Indexed as

Computational BiologyMetabolomeSoftwareHumans

Identifiers

PMID32209698
PMCPMC7331181

What OpenQuestion holds

Textmetadata
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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 OpenQuestion graph.