Evidence map›Paper›PMID 39699184›Full record

ArticlemSystems2025

Modification and analysis of context-specific genome-scale metabolic models: methane-utilizing microbial chassis as a case study.

M A Kulyashov, R Hamilton, Y Afshin, S K Kolmykov, T S Sokolova, T M Khlebodarova, M G Kalyuzhnaya, I R Akberdin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in mSystems, 2025. 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

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

1 citing paper in PubMed.

  1. Review
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

8 authors.

M A Kulyashov *Department of Computational Biology, Scientific Center for Genetics and Life Sciences, Sirius University of Science and Technology, Sochi, Russia.
R Hamilton *Department of Biology and Viral Information Institute, San Diego State University, San Diego, California, USA.
Y AfshinDepartment of Biology and Viral Information Institute, San Diego State University, San Diego, California, USA.
S K KolmykovDepartment of Computational Biology, Scientific Center for Genetics and Life Sciences, Sirius University of Science and Technology, Sochi, Russia.
T S SokolovaDepartment of Computational Biology, Scientific Center for Genetics and Life Sciences, Sirius University of Science and Technology, Sochi, Russia.
T M KhlebodarovaDepartment of Computational Biology, Scientific Center for Genetics and Life Sciences, Sirius University of Science and Technology, Sochi, Russia.
M G KalyuzhnayaDepartment of Biology and Viral Information Institute, San Diego State University, San Diego, California, USA.ORCID 0000-0002-9058-7794
I R AkberdinDepartment of Computational Biology, Scientific Center for Genetics and Life Sciences, Sirius University of Science and Technology, Sochi, Russia.ORCID 0000-0003-0010-8620

Funding

Russian Science Foundation (RSF) 23-24-00606U.S. Department of Energy (DOE) DE-SC0019181
6 · The paper itself

Abstract

Context-specific genome-scale model (CS-GSM) reconstruction is becoming an efficient strategy for integrating and cross-comparing experimental multi-scale data to explore the relationship between cellular genotypes, facilitating fundamental or applied research discoveries. However, the application of CS modeling for non-conventional microbes is still challenging. Here, we present a graphical user interface that integrates COBRApy, EscherPy, and RIPTiDe, Python-based tools within the BioUML platform, and streamlines the reconstruction and interrogation of the CS genome-scale metabolic frameworks via Jupyter Notebook. The approach was tested using -omics data collected for IMPORTANCE: The interrogation of various types of data is a routine strategy to explore the relationship between genotype and phenotype. An efficient approach for integrating and cross-comparing experimental multi-scale data in the context of whole-genome-based metabolic network reconstruction becomes a powerful tool that facilitates fundamental and applied research discoveries. The present study describes the reconstruction of a context-specific (CS) model for the methane-utilizing bacterium,

Indexed as

Genome, BacterialMethaneMethylococcaceaeModels, BiologicalMetabolic Networks and PathwaysMethanecontext-specific genome-scale metabolic modelingmethane-utilizing bacteriamethanotrophyMethylotuvimicrobium alcaliphilum 20ZR

Identifiers

PMID39699184
PMCPMC11748545

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.