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The Modelling and Inference of MICrobiomes Project (MIMIC) introduces a Python package designed to advance the simulation, inference, and prediction of microbial community interactions and dynamics. Addressing the complex nature of microbial ecosystems, MIMIC integrates a suite of mathematical models, including previously used approaches such as Generalized Lotka-Volterra (gLV), Gaussian Processes (GP), and Vector Autoregression (VAR) plus newly developed models for integrating multi-omic data, to offer a versatile framework for analyzing microbial dynamics. By leveraging Bayesian inference and machine learning techniques, MIMIC provides the ability to infer the dynamics of microbial communities from empirical data, facilitating a deeper understanding of their complex biological processes, unveiling possible unknown ecological interactions, and enabling the design of microbial communities. Such insights could help to advance microbial ecology research, optimizing biotechnological applications, and contribute to environmental sustainability and public health strategies. MIMIC is designed for flexibility and ease of use, aiming to support researchers and practitioners in microbial ecology and microbiome research.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>MIMIC is freely available under the MIT License at https:\/\/github.com\/ucl-cssb\/MIMIC. It is implemented in Python (version 3.7 or higher) and is compatible with Windows, macOS, and Linux operating systems. MIMIC depends on standard Python libraries including NumPy, SciPy, and PyMC. Comprehensive examples and tutorials (including the main text demonstrations) are provided as Jupyter notebooks in the examples\/directory and at the MIMIC Docs website, along with detailed installation instructions and real-world data use cases. The software will remain freely available for at least two years following publication. A code snapshot for this publication is also available at Zenodo: https:\/\/doi.org\/10.5281\/zenodo.15149003.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaf174","type":"journal-article","created":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T15:58:05Z","timestamp":1748015885000},"source":"Crossref","is-referenced-by-count":2,"title":["MIMIC: a Python package for simulating, inferring, and predicting microbial community interactions and dynamics"],"prefix":"10.1093","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0535-2684","authenticated-orcid":false,"given":"Pedro","family":"Fontanarrosa","sequence":"first","affiliation":[{"name":"Research Department of Cell and Developmental Biology, University College London , London, WC1E 6BT,","place":["United Kingdom"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5788-7453","authenticated-orcid":false,"given":"Chania","family":"Clare","sequence":"additional","affiliation":[{"name":"Research Department of Cell and Developmental Biology, University College London , London, WC1E 6BT,","place":["United Kingdom"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0165-1705","authenticated-orcid":false,"given":"Alex J H","family":"Fedorec","sequence":"additional","affiliation":[{"name":"Research Department of Cell and Developmental Biology, University College London , London, WC1E 6BT,","place":["United Kingdom"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9459-1395","authenticated-orcid":false,"given":"Chris P","family":"Barnes","sequence":"additional","affiliation":[{"name":"Research Department of Cell and Developmental Biology, University College London , London, WC1E 6BT,","place":["United Kingdom"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2025,5,23]]},"reference":[{"key":"2025052819562614000_btaf174-B1","doi-asserted-by":"publisher","first-page":"15718","DOI":"10.1073\/pnas.0407076101","article-title":"The gut microbiota as an environmental factor that regulates fat storage","volume":"101","author":"B\u00e4ckhed","year":"2004","journal-title":"Proc Natl Acad Sci USA"},{"key":"2025052819562614000_btaf174-B2","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1186\/s13059-016-0980-6","article-title":"MDSINE: Microbial Dynamical Systems INference Engine for microbiome time-series analyses","volume":"17","author":"Bucci","year":"2016","journal-title":"Genome Biol"},{"key":"2025052819562614000_btaf174-B3","doi-asserted-by":"crossref","first-page":"1600188","DOI":"10.1002\/bies.201600188","article-title":"Inferring human microbial dynamics from temporal metagenomics data: pitfalls and lessons","volume":"39","author":"Cao","year":"2017","journal-title":"Bioessays"},{"key":"2025052819562614000_btaf174-B4","doi-asserted-by":"publisher","first-page":"R50","DOI":"10.1186\/gb-2011-12-5-r50","article-title":"Moving pictures of the human microbiome","volume":"12","author":"Caporaso","year":"2011","journal-title":"Genome Biol"},{"key":"2025052819562614000_btaf174-B5","doi-asserted-by":"crossref","first-page":"2647","DOI":"10.1038\/s41396-019-0459-z","article-title":"Use and abuse of correlation analyses in microbial ecology","volume":"13","author":"Carr","year":"2019","journal-title":"ISME J"},{"key":"2025052819562614000_btaf174-B6","first-page":"73","author":"Carvalho","year":"2009"},{"key":"2025052819562614000_btaf174-B7","doi-asserted-by":"crossref","first-page":"1454","DOI":"10.1038\/s41592-024-02359-7","article-title":"Applying interpretable machine learning in computational biology\u2014pitfalls, recommendations and opportunities for new developments","volume":"21","author":"Chen","year":"2024","journal-title":"Nat Methods"},{"key":"2025052819562614000_btaf174-B8","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1111\/j.1365-2982.2010.01664.x","article-title":"The microbiome-gut-brain axis: from bowel to behavior","volume":"23","author":"Cryan","year":"2011","journal-title":"Neurogastroenterol Motility"},{"key":"2025052819562614000_btaf174-B9","doi-asserted-by":"crossref","first-page":"e0075722","DOI":"10.1128\/msystems.00757-22","article-title":"When does a Lotka-Volterra model represent microbial interactions? 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