ArticleThe ISME journal2017
Modeling time-series data from microbial communities.
Article in The ISME journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- A Bayesian functional concurrent zero-inflated Dirichlet-multinomial regression model with application to infant microbiome.Biostatistics (Oxford, England) · 2026Article
- Resilience of a stochastic generalized Lotka-Volterra model for microbiome studies.Mathematical biosciences and engineering : MBE · 2025Article
- Complex system modeling reveals oxalate homeostasis is driven by diverse oxalate-degrading bacteria.eLife · 2025Article
- Eco-evolutionary robustness of wild bacterial communities to experimental perturbation.The ISME journal · 2025Article
- Article
- Methodological Considerations in Longitudinal Analyses of Microbiome Data: A Comprehensive Review.Genes · 2023Review
- Microbial Growth under Limiting Conditions-Future Perspectives.Microorganisms · 2023Review
- DeepMicroGen: a generative adversarial network-based method for longitudinal microbiome data imputation.Bioinformatics (Oxford, England) · 2023Article
- Prediction and analysis of time series data based on granular computing.Frontiers in computational neuroscience · 2023Article
- An evaluation of homeostatic plasticity for ecosystems using an analytical data science approach.Computational and structural biotechnology journal · 2023Review
- Fusarium oxysporum Disrupts Microbiome-Metabolome Networks in Arabidopsis thaliana Roots.Microbiology spectrum · 2022Article
- Using Community Ecology Theory and Computational Microbiome Methods To Study Human Milk as a Biological System.mSystems · 2022Review
- Functional response regression model on correlated longitudinal microbiome sequencing data.Statistical methods in medical research · 2022Article
- Temporal Alignment of Longitudinal Microbiome Data.Frontiers in microbiology · 2022Article
- Modeling Microbial Community Networks: Methods and Tools.Current genomics · 2021Review
- Microbial trend analysis for common dynamic trend, group comparison, and classification in longitudinal microbiome study.BMC genomics · 2021Article
- Towards a deeper understanding of microbial communities: integrating experimental data with dynamic models.Current opinion in microbiology · 2021Review
- Structural identifiability of the generalized Lotka-Volterra model for microbiome studies.Royal Society open science · 2021Article
- Cystic fibrosis airway microbiota associated with outcomes of nontuberculous mycobacterial infection.ERJ open research · 2021Article
- Challenges, Strategies, and Perspectives for Reference-Independent Longitudinal Multi-Omic Microbiome Studies.Frontiers in genetics · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
As sequencing technologies have advanced, the amount of information regarding the composition of bacterial communities from various environments (for example, skin or soil) has grown exponentially. To date, most work has focused on cataloging taxa present in samples and determining whether the distribution of taxa shifts with exogenous covariates. However, important questions regarding how taxa interact with each other and their environment remain open thus preventing in-depth ecological understanding of microbiomes. Time-series data from 16S rDNA amplicon sequencing are becoming more common within microbial ecology, but methods to infer ecological interactions from these longitudinal data are limited. We address this gap by presenting a method of analysis using Poisson regression fit with an elastic-net penalty that (1) takes advantage of the fact that the data are time series; (2) constrains estimates to allow for the possibility of many more interactions than data; and (3) is scalable enough to handle data consisting of thousands of taxa. We test the method on gut microbiome data from white-throated woodrats (Neotoma albigula) that were fed varying amounts of the plant secondary compound oxalate over a period of 22 days to estimate interactions between OTUs and their environment.
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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.