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Bayesian compositional regression with microbiome features via variational inference
The microbiome plays a key role in the health of the human body. Interest often lies in finding features of the microbiome, alongside other...
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The parieto-occipital cortex is a candidate neural substrate for the human ability to approximate Bayesian inference
Adaptive decision-making often requires one to infer unobservable states based on incomplete information. Bayesian logic prescribes that individuals...
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NestedBD: Bayesian inference of phylogenetic trees from single-cell copy number profiles under a birth-death model
Copy number aberrations (CNAs) are ubiquitous in many types of cancer. Inferring CNAs from cancer genomic data could help shed light on the...
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Bayesian Inference of Soil Traits from Green Manure Fields in a Tropical Sandy Soil
Green manure represents a crucial soil management practice for soil traits and potentially sequestering organic carbon (OC) within the soil profile....
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Inference about quantitative traits under selection: a Bayesian revisitation for the post-genomic era
BackgroundSelection schemes distort inference when estimating differences between treatments or genetic associations between traits, and may degrade...
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Early cephalopod evolution clarified through Bayesian phylogenetic inference
BackgroundDespite the excellent fossil record of cephalopods, their early evolution is poorly understood. Different, partly incompatible phylogenetic...
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Gene regulatory network inference based on a nonhomogeneous dynamic Bayesian network model with an improved Markov Monte Carlo sampling
A nonhomogeneous dynamic Bayesian network model, which combines the dynamic Bayesian network and the multi-change point process, solves the...
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Beyond the Michaelis–Menten: Bayesian Inference for Enzyme Kinetic Analysis
Although the Michaelis–Menten (MM) rate law has been widely used to estimate enzyme kinetic parameters, it works only under the condition of...
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On the use of prior distributions in bayesian inference applied to Ecology: an ecological example using binomial proportions in exotic plants, Central Chile
BackgroundThe use of Bayesian inference (BI) is a common methodology for data analysis in Ecology and Evolution. This statistical approach is...
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Belief inference for hierarchical hidden states in spatial navigation
Uncertainty abounds in the real world, and in environments with multiple layers of unobservable hidden states, decision-making requires resolving...
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Bayesian inference for identifying tumour-specific cancer dependencies through integration of ex-vivo drug response assays and drug-protein profiling
The identification of tumor-specific molecular dependencies is essential for the development of effective cancer therapies. Genetic and chemical...
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Identifying spatio-temporal seizure propagation patterns in epilepsy using Bayesian inference
Focal drug resistant epilepsy is a neurological disorder characterized by seizures caused by abnormal activity originating in one or more regions...
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Multiple-trait model through Bayesian inference applied to flood-irrigated rice (Oryza sativa L)
The objectives of this study were to use a bayesian multi-trait model, estimate genetic parameters, and select flood-irrigated rice genotypes with...
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Consensus clustering for Bayesian mixture models
BackgroundCluster analysis is an integral part of precision medicine and systems biology, used to define groups of patients or biomolecules....
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PMF-GRN: a variational inference approach to single-cell gene regulatory network inference using probabilistic matrix factorization
Inferring gene regulatory networks (GRNs) from single-cell data is challenging due to heuristic limitations. Existing methods also lack estimates of...
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Multivariate EEG activity reflects the Bayesian integration and the integrated Galilean relative velocity of sensory motion during sensorimotor behavior
Humans integrate multiple sources of information for action-taking, using the reliability of each source to allocate weight to the data. This...
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Bayesian inference of root architectural model parameters from synthetic field data
Background and aimsCharacterizing root system architectures of field-grown crops is challenging as root systems are hidden in the soil. We...
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Causal impact of fire on a globally rare wetland plant: a 40-year Bayesian time series analysis
BackgroundCanby’s dropwort ( Oxypolis canbyi (J.M. Coult. & Rose) Fernald) was listed as federally endangered in 1986, yet the species has continued...
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An Integrated Bayesian-Heuristic Semiotic Model for Understanding Human and SARS-CoV-2 Representational Structures
The aim of this paper is to explore the connections between semiotics and biology by examining the behaviors of both humans and non-cognizant agents,...
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VBASS enables integration of single cell gene expression data in Bayesian association analysis of rare variants
Rare or de novo variants have substantial contribution to human diseases, but the statistical power to identify risk genes by rare variants is...
