ArticleFrontiers in microbiology2014
Hidden state prediction: a modification of classic ancestral state reconstruction algorithms helps unravel complex symbioses.
Article in Frontiers in microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Predicting gene distribution in ammonia-oxidizing archaea using phylogenetic signals.ISME communications · 2025Article
- An evolutionary case for plant rarity:Ecology and evolution · 2024Article
- The impact of lactic acid bacteria inoculation on the fermentation and metabolomic dynamics of indigenous Beijing douzhi microbial communities.Frontiers in microbiology · 2024Article
- Accounting for 16S rRNA copy number prediction uncertainty and its implications in bacterial diversity analyses.ISME communications · 2023Article
- Organelle 16S rRNA amplicon sequencing enables profiling of active gut microbiota in murine model.Applied microbiology and biotechnology · 2022Article
- The differences of bacterial communities in the tissues between healthy and diseased Yesso scallop (Patinopecten yessoensis).AMB Express · 2019Article
- Trait-based community assembly and succession of the infant gut microbiome.Nature communications · 2019Article
- Correcting for 16S rRNA gene copy numbers in microbiome surveys remains an unsolved problem.Microbiome · 2018Article
- Overfishing and nutrient pollution interact with temperature to disrupt coral reefs down to microbial scales.Nature communications · 2016Article
- Predicting microbial traits with phylogenies.The ISME journal · 2016Article
- PanFP: pangenome-based functional profiles for microbial communities.BMC research notes · 2015Article
- Natural volcanic CO2 seeps reveal future trajectories for host-microbial associations in corals and sponges.The ISME journal · 2015Article
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2 authors.
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Abstract
Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP), and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses.
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