Evidence map›Paper›PMID 35689204›Full record

ArticleBMC bioinformatics2022

Linear programming based gene expression model (LPM-GEM) predicts the carbon source for Bacillus subtilis.

Kulwadee Thanamit, Franziska Hoerhold, Marcus Oswald, Rainer Koenig

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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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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

1 citing paper 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

4 authors.

Kulwadee ThanamitSystems Biology Research Group, Institute for Infectious Diseases and Infection Control (IIMK), Jena University Hospital, Kollegiengasse 10, 07743, Jena, Germany.
Franziska HoerholdSystems Biology Research Group, Institute for Infectious Diseases and Infection Control (IIMK), Jena University Hospital, Kollegiengasse 10, 07743, Jena, Germany.
Marcus OswaldSystems Biology Research Group, Institute for Infectious Diseases and Infection Control (IIMK), Jena University Hospital, Kollegiengasse 10, 07743, Jena, Germany.
Rainer KoenigSystems Biology Research Group, Institute for Infectious Diseases and Infection Control (IIMK), Jena University Hospital, Kollegiengasse 10, 07743, Jena, Germany. Rainer.Koenig@uni-jena.de.

Funding

Bundesministerium für Bildung und Forschung 01EO1502)Bundesministerium für Bildung und Forschung Care (01EO1002Bundesministerium für Bildung und Forschung Center for Sepsis ControlDeutsche Forschungsgemeinschaft KO 3678/5-1
6 · The paper itself

Abstract

backgroundElucidating cellular metabolism led to many breakthroughs in biotechnology, synthetic biology, and health sciences. To date, deriving metabolic fluxes by

resultWe established the novel method Linear Programming based Gene Expression Model (LPM-GEM). LPM-GEM linearly embeds gene expression into FBA constraints. We implemented three strategies to reduce thermodynamically infeasible loops, which is a necessary prerequisite for such an omics-based model building. As a case study, we built a model of B. subtilis grown in eight different carbon sources. We obtained good flux predictions based on the respective transcription profiles when validating with

conclusionEmploying LPM-GEM integrates gene expression data efficiently. The method supports gene expression-based FBA models and can be applied as an alternative to estimate metabolic fluxes when tracer experiments are inappropriate.

Indexed as

Bacillus subtilisCarbonGene ExpressionMetabolic Networks and PathwaysModels, BiologicalProgramming, LinearCarbonBacillus subtilisCarbon sourceConstraint-based modelingFlux balance analysisMixed-integer linear programmingThermodynamically infeasible loopsTranscriptomics

Identifiers

PMID35689204
PMCPMC9188260

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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.