ArticleBMC molecular and cell biology2020
IMPARO: inferring microbial interactions through parameter optimisation.
Article in BMC molecular and cell biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 12 citations in OpenAlex.
- A model of early-life interactions between the gut microbiome and adaptive immunity provides insights into the ontogeny of immune tolerance.PLoS biology · 2025Article
- The MTIST platform: a microbiome time series inference standardized test.Research square · 2024Article
- Microbiome distribution modeling using gradient descent strategies for mock, in vitro and clinical community distributions.PloS one · 2023Article
- Vaginal microbiota networks as a mechanistic predictor of aerobic vaginitis.Frontiers in microbiology · 2022Article
- Microbial communities in the liver and brain are informative for postmortem submersion interval estimation in the late phase of decomposition: A study in mouse cadavers recovered from freshwater.Frontiers in microbiology · 2022Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMicrobial Interaction Networks (MINs) provide important information for understanding bacterial communities. MINs can be inferred by examining microbial abundance profiles. Abundance profiles are often interpreted with the Lotka Volterra model in research. However existing research fails to consider a biologically meaningful underlying mathematical model for MINs or to address the possibility of multiple solutions.
resultsIn this paper we present IMPARO, a method for inferring microbial interactions through parameter optimisation. We use biologically meaningful models for both the abundance profile, as well as the MIN. We show how multiple MINs could be inferred with similar reconstructed abundance profile accuracy, and argue that a unique solution is not always satisfactory. Using our method, we successfully inferred clear interactions in the gut microbiome which have been previously observed in in-vitro experiments.
conclusionsIMPARO was used to successfully infer microbial interactions in human microbiome samples as well as in a varied set of simulated data. The work also highlights the importance of considering multiple solutions for MINs.
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