ArticlemSystems2021
Dynamic Bayesian Networks for Integrating Multi-omics Time Series Microbiome Data.
Article in mSystems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it, 53 citations in OpenAlex.
- Multi-omics time-series analysis in microbiome research: a systematic review.Briefings in bioinformatics · 2025Pooled it
- Microbial and enzymatic synergy in fermented fish: impacts on flavor, texture, and safety with multi-omics and AI insights.Food chemistry: X · 2026Review
- From association to causation: a decision-aware framework for reproducible biomarker discovery and precision intervention design in the human gut microbiome.Briefings in bioinformatics · 2026Article
- Water kefir as a paradigm for multi-omics and genome-scale metabolic modelling in fermented food.NPJ biofilms and microbiomes · 2026Review
- Article
- Global Distribution and Dispersal Pathways of Riparian Invasives: Perspectives Using Alligator Weed (Plants (Basel, Switzerland) · 2026Review
- Design, processing, and modeling for longitudinal multiomics microbiome data.Frontiers in cellular and infection microbiology · 2026Review
- Network-informed deconvolution of bulk immune gene co-expression reveals single-cell programs and spatial organization.Frontiers in immunology · 2026Article
- Targeting the gut microbiota: emerging strategies to enhance healing of diabetic foot ulcers.Frontiers in endocrinology · 2026Review
- GGut microbes · 2025Review
- A Novel Integrative Framework for Depression: Combining Network Pharmacology, Artificial Intelligence, and Multi-Omics with a Focus on the Microbiota-Gut-Brain Axis.Current issues in molecular biology · 2025Review
- Multi-omics mediation pipeline reveals differential pathways of maternal SNPs affecting newborn adiposity outcomes.BMC genomic data · 2025Article
- Generative model for the first cell fate bifurcation in mammalian development.Development (Cambridge, England) · 2025Article
- Distinct gut microbiota profiles and network properties in older Korean individuals with subjective cognitive decline, mild cognitive impairment, and Alzheimer's disease.Alzheimer's research & therapy · 2025Article
- Current Bioinformatics Tools in Precision Oncology.MedComm · 2025Review
- Comprehensive review of Bayesian network applications in gastrointestinal cancers.World journal of clinical oncology · 2025Review
- How quantum computing can enhance biomarker discovery.Patterns (New York, N.Y.) · 2025Review
- LEOPARD: missing view completion for multi-timepoint omics data via representation disentanglement and temporal knowledge transfer.Nature communications · 2025Article
- Article
- Utility of Machine Learning to Characterize Gut Microbiota Dysbiosis and Its Clinical Implications in Inflammatory Bowel Disease.Journal of inflammation research · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
A key challenge in the analysis of longitudinal microbiome data is the inference of temporal interactions between microbial taxa, their genes, the metabolites that they consume and produce, and host genes. To address these challenges, we developed a computational pipeline, a pipeline for the analysis of longitudinal multi-omics data (PALM), that first aligns multi-omics data and then uses dynamic Bayesian networks (DBNs) to reconstruct a unified model. Our approach overcomes differences in sampling and progression rates, utilizes a biologically inspired multi-omic framework, reduces the large number of entities and parameters in the DBNs, and validates the learned network. Applying PALM to data collected from inflammatory bowel disease patients, we show that it accurately identifies known and novel interactions. Targeted experimental validations further support a number of the predicted novel metabolite-taxon interactions.
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What OpenQuestion holds
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.