Evidence map›Paper›PMID 33602294›Full record

ReviewGenome biology2021

Addressing uncertainty in genome-scale metabolic model reconstruction and analysis.

David B Bernstein, Snorre Sulheim, Eivind Almaas, Daniel Segrè

Abstract readReview
In one paragraph

Review in Genome biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers.

0numbers the graph read from it
0cells of the map it votes in
80citing 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

80 citing papers in PubMed.

  1. Article
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  10. Computational and structural biotechnology journal · 2026
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  15. Review
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20 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

4 authors.

David B Bernstein *Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, USA.
Snorre Sulheim *Bioinformatics Program, Boston University, Boston, MA, USA.
Eivind AlmaasDepartment of Biotechnology and Food Science, NTNU - Norwegian University of Science and Technology, Trondheim, Norway.
Daniel SegrèDepartment of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, USA. dsegre@bu.edu.ORCID 0000-0003-4859-1914

Funding

Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategiesUH2AG064704 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI PERLS, THOMAS T, SEBASTIANI, PAOLA · 2019 to 2021
$9.4M
Cultivation, Nature, Ecology and Pathogenicity of the Uncultivable Oral MicrobiomR01DE024468 · NIDCR · ADA FORSYTH INSTITUTE, INC. · PI ALM, ERIC JOHN, DEWHIRST, FLOYD E · 2014 to 2018
$7.3M
TRAINING PROGRAM IN QUANTITATIVE BIOLOGY AND PHYSIOLOGYT32GM008764 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI WHITE, JOHN A. · 2001 to 2021
$5.9M
NIA NIH HHS UH2 AG064704NIDCR NIH HHS R01 DE024468NIGMS NIH HHS T32 GM008764NIGMS NIH HHS T32GM008764
6 · The paper itself

Abstract

The reconstruction and analysis of genome-scale metabolic models constitutes a powerful systems biology approach, with applications ranging from basic understanding of genotype-phenotype mapping to solving biomedical and environmental problems. However, the biological insight obtained from these models is limited by multiple heterogeneous sources of uncertainty, which are often difficult to quantify. Here we review the major sources of uncertainty and survey existing approaches developed for representing and addressing them. A unified formal characterization of these uncertainties through probabilistic approaches and ensemble modeling will facilitate convergence towards consistent reconstruction pipelines, improved data integration algorithms, and more accurate assessment of predictive capacity.

Indexed as

Energy MetabolismModels, BiologicalAlgorithmsBiomassComputational BiologyEnvironmentGene-Environment InteractionGenome-Wide Association StudyGenomicsHumansMetabolic Networks and PathwaysMolecular Sequence AnnotationSystems Biology

Identifiers

PMID33602294
PMCPMC7890832

What OpenQuestion holds

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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.