ArticleeLife2022
Machine learning-assisted discovery of growth decision elements by relating bacterial population dynamics to environmental diversity.
Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled 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.
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.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Bibliometric analysis of the application of artificial intelligence techniques in bacteriology: a PRISMA-guided research agenda.Frontiers in microbiology · 2025Pooled it
- A logistic model for glucose‑driven asymmetry in multi‑phase E. coli growth kinetics.Scientific reports · 2026Article
- Growth dynamics of 3,909 Escherichia coli single-gene knockouts in rich and minimal media.Scientific data · 2026Article
- Time Series Data Mining for Linking the Shape of Bacterial Growth Curves to Biological Functions.Computational and structural biotechnology journal · 2026Article
- Data-driven analysis reveals distinct genomic and environmental contributions to bacterial growth curves.Scientific reports · 2025Article
- Experimental mapping of bacterial fitness landscapes reveals eco-evolutionary fingerprints.Scientific reports · 2025Article
- Systematic selection of best performing mathematical models for in vitro gas production using machine learning across diverse feeds.Scientific reports · 2025Article
- Translating microbial kinetics into quantitative responses and testable hypotheses using Kinbiont.Nature communications · 2025Article
- Population Dynamics of Escherichia coli Growing under Chemically Defined Media.Scientific data · 2025Article
- Data-driven discovery of the interplay between genetic and environmental factors in bacterial growth.Communications biology · 2024Article
- Immunosenescence: How Aging Increases Susceptibility to Bacterial Infections and Virulence Factors.Microorganisms · 2024Review
- Article
- Nine (not so simple) steps: a practical guide to using machine learning in microbial ecology.mBio · 2024Review
- A machine learning-based strategy to elucidate the identification of antibiotic resistance in bacteria.Frontiers in antibiotics · 2024Article
- Autoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics.Nature communications · 2023Article
- Review
- Employing active learning in the optimization of culture medium for mammalian cells.NPJ systems biology and applications · 2023Article
- Machine learning-assisted medium optimization revealed the discriminated strategies for improved production of the foreign and native metabolites.Computational and structural biotechnology journal · 2023Article
- Growth rate-associated transcriptome reorganization in response to genomic, environmental, and evolutionary interruptions.Frontiers in microbiology · 2023Article
- Global coordination of the mutation and growth rates across the genetic and nutritional variety inFrontiers in microbiology · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microorganisms growing in their habitat constitute a complex system. How the individual constituents of the environment contribute to microbial growth remains largely unknown. The present study focused on the contribution of environmental constituents to population dynamics via a high-throughput assay and data-driven analysis of a wild-type
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Registered trials
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.