ArticleeLife2022
Recurrent neural networks enable design of multifunctional synthetic human gut microbiome dynamics.
Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
- Decoding the microbiome: artificial intelligence-targeted gut microenvironment breakthroughs in personalized cancer therapy.Gut microbes · 2026Review
- Integrating host-microbiome multi-omics with machine learning: methods, benchmarks, and translational applications.Science China. Life sciences · 2026Review
- Rational assembly of synthetic marine biofilm community with chitinase production.Research square · 2026Article
- Advances and future directions in identifying specific taxa from microbial meta-omics data: from pipeline to deep learning.mSystems · 2026Review
- Dynamical Systems-Constrained Metabolic Modeling Enables Forecasting of Host-Microbiome Dynamics.bioRxiv : the preprint server for biology · 2026Article
- Physics-constrained neural ordinary differential equation models to discover and predict microbial community dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Soil microbiome prediction using traditional machine learning and deep learning models.Scientific reports · 2026Article
- Artificial intelligence in functional food innovation: Bioactive enhancement and formulation optimization: A quasi-systematic review.Food chemistry: X · 2026Review
- Metabolic blueprints of monocultures enable prediction and design of synthetic microbial consortia.bioRxiv : the preprint server for biology · 2026Article
- Decoding host-microbiome interactions through integrative multi-omics and artificial intelligence: from biological mechanisms to predictive modelling.Frontiers in microbiomes · 2026Review
- Integrative artificial intelligence and multi-omics modeling approach for characterizing microbial dynamics and health impacts in space microgravity and radiation conditions.Frontiers in microbiology · 2026Article
- Statistical design of a synthetic microbiome that suppresses diverse gut pathogens.bioRxiv : the preprint server for biology · 2025Article
- Artificial intelligence empowers gut microbiota research in neurodegenerative diseases molecular mechanisms and precision therapy.iScience · 2025Review
- A foundation model for microbial growth dynamics.bioRxiv : the preprint server for biology · 2025Article
- Review
- Predicting microbial community structure and temporal dynamics by using graph neural network models.Nature communications · 2025Article
- Unravelling three-way interactions betweenJournal of medical microbiology · 2025Review
- Smart Microbiomes: How AI Is Revolutionizing Personalized Medicine.Bioengineering (Basel, Switzerland) · 2025Review
- Targeted Intervention Strategies for Maternal-Offspring Transmission of Christensenellaceae in Pigs via a Deep Learning Model.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Decoding the role of the arginine dihydrolase pathway in shaping human gut community assembly and health-relevant metabolites.Cell systems · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Predicting the dynamics and functions of microbiomes constructed from the bottom-up is a key challenge in exploiting them to our benefit. Current models based on ecological theory fail to capture complex community behaviors due to higher order interactions, do not scale well with increasing complexity and in considering multiple functions. We develop and apply a long short-term memory (LSTM) framework to advance our understanding of community assembly and health-relevant metabolite production using a synthetic human gut community. A mainstay of recurrent neural networks, the LSTM learns a high dimensional data-driven non-linear dynamical system model. We show that the LSTM model can outperform the widely used generalized Lotka-Volterra model based on ecological theory. We build methods to decipher microbe-microbe and microbe-metabolite interactions from an otherwise black-box model. These methods highlight that Actinobacteria, Firmicutes and Proteobacteria are significant drivers of metabolite production whereas
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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.