Evidence map›Paper›PMID 42095649›Full record

ArticlemSystems2026

Machine learning reveals proteome-encoded growth determinants underlying metabolic versatility of

Abraham Osinuga, Mark Kathol, Rajib Saha

Abstract read
In one paragraph

Article in mSystems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Abraham OsinugaDepartment of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.ORCID 0000-0002-2587-8704
Mark KatholDepartment of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.
Rajib SahaDepartment of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.ORCID 0000-0002-2974-0243

Funding

National Science Foundation Career Grant 1943310NIH HHS MIRA Award (5R35GM143009)
6 · The paper itself

Abstract

Lignin depolymerization generates mixtures of aromatic compounds that are promising carbon sources for microbial bioconversion, yet the constraints governing microbial growth on these substrates remain unclear. Here, we investigated how

Indexed as

Bacterial ProteinsLigninMachine LearningProteomeRhodopseudomonasProteomicsBacterial ProteinsLigninProteomegrowth predictionslignin breakdown productsmachine learningmetabolic versatilityproteomicsRhodopseudomonas palustris

Identifiers

PMID42095649
PMCPMC13289028

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.