Bayesian inference

Using Bayesian inference to characterize cell-size regulation across organisms

This paper develops a Bayesian framework to accurately infer cell-size regulation strategies by accounting for noise and variability, showing that previous methods were biased and that adder-like regulation is more consistent across organisms.

Spatio-temporal modeling of an insect vector distribution

This study estimates the spatiotemporal distribution of the Monochamus galloprovincialis insect vector in France using Bayesian models and environmental data to improve pinewood nematode surveillance.

Climate-driven decoupling of a coevolved mutualism between Joshua trees (Yucca brevifolia and Y. jaegeriana, Asparagaceae) and pollinating yucca moths (Tegeticula synthetica and T. antithetica, Prodoxidae)

The paper uses Bayesian models to analyze how climate change affects the flowering and fruiting of Joshua trees and their pollinating moths, finding a mismatch in their responses to temperature and precipitation.

Bayesian spatial prediction of three medically important tick species in Illinois

The paper uses Bayesian hierarchical spatial models to predict the relative abundance of three tick species in Illinois based on environmental and spatial data.

Bayesian phylogenetics with incomplete lineage tracing data

This paper introduces a Bayesian framework to improve phylogenetic inference from sparse lineage tracing data by modeling barcode loss, showing it enhances accuracy and recovers higher growth rates than standard filtering methods.

CaPri: Bayesian Mendelian randomization for joint estimation of causal and pleiotropic effects

CaPri is a Bayesian Mendelian randomization framework that jointly estimates causal and pleiotropic effects, showing robust performance across varying pleiotropy proportions and real data applications.

Joint Variable Selection for Omic Biomarkers in Time-to-Event Data

The paper introduces vampW, a Bayesian method for joint variable selection in omic biomarkers and time-to-event data, showing reduced false discoveries and improved prediction.

Efficient approximate Bayesian inference for large, heterogeneous biological datasets

The paper introduces an adaptive minibatch approach for approximate Bayesian inference, improving speed-precision tradeoffs for large, heterogeneous biological datasets.

Covariance Nonstationarity is Evident in Spatial Transcriptomics and Provides a New Categorization of Spatially Varying Genes

The paper assesses covariance stationarity in spatial transcriptomics and identifies spatially varying genes using non-stationary covariance models.

Application of Bayesian-Derived Gene Interaction Network and Subnetwork for Classification of Idiopathic Parkinson Disease with Biomarkers

The paper develops a Bayesian gene interaction network to identify 13 genes for PD classification, achieving high AUC in a blood-based transcriptomic analysis of the PPMI cohort.

Retinal arteriolar tortuosity as a candidate genetic window to inner-ear microvasculature: distributed sharing with blood pressure at CSK and PAWR and a roadmap for larger hearing GWAS

This paper investigates the genetic link between retinal arteriolar tortuosity and blood pressure, identifying potential shared genetic loci and suggesting retinal microvasculature as a candidate window for inner-ear microvasculature studies.

A Bayesian approach to volumetric analysis in rare neurodegenerative disorders

This paper applies Bayesian hierarchical modeling to assess regional brain atrophy in rare neurodegenerative disorders, finding significant volume loss in specific brain regions across disease groups.

Gene-level evolutionary conservation and human constraint decline at comparable rates across the age of onset of Mendelian disease

The paper compares the rate of decline in gene-level evolutionary conservation and human constraint scores with disease onset age across Mendelian diseases.

Empirical Bayes Estimation of Sample-Specific Correlation Networks for Cross-Sectional and Longitudinal Omics Data

PRISM estimates sample-specific correlation networks for cross-sectional and longitudinal omics data, improving accuracy and uncertainty quantification over existing methods.

Multi-Trajectory Pseudotime Inference via Permutation Factorizations

Factorizing multiple monotone pseudotimes into one shared donor permutation plus cluster-specific warps (HiP-BIND) yields Alzheimer's donor orderings agreeing better with Braak, ADNC and CERAD staging than single-trajectory B-BIND.

Making Biorisk Measurable: A Bayesian Framework for Laboratory Risk Management

This paper introduces a Bayesian framework for laboratory risk management that quantifies biosafety risk using a log-risk scale and incorporates WHO Risk Group classifications and incident escalation models.

LGTM: Gaussian Process Modulated Neural Topic Modeling for Longitudinal Microbiome

LGTM couples a neural topic model with additive basis-function Gaussian processes, learning microbial co-abundance topics and how covariates relate to their trajectories in longitudinal gut microbiome data.

An information-borrowing Bayesian method for inferring high-dimensional population-level brain connectivity from small samples

The paper introduces a Bayesian method for estimating population-level brain connectivity from small samples, showing improved accuracy over existing methods in simulations and real data.

The limits of Bayesian estimates of divergence times in measurably evolving populations

This paper examines the limits of Bayesian divergence time estimates in microbial evolution, finding that uncertainty scales with distance to calibration points rather than absolute age.

Accurate detection of metagenomic strain-level associations using average nucleotide identity with StrainSpy

StrainSpy fits zero-inflated beta mixed models to containment ANI, reaching >98% simulated sensitivity versus ~79% for logistic regression and detecting colorectal-cancer E. coli strain shifts.

BOSE: A Bayesian Order Statistics-Based Estimator for Recovering the Sample Mean and Standard Deviation from the Median, Range, and/or Interquartile Range

BOSE estimates sample mean and standard deviation from median, range, and interquartile range using Bayesian order statistics, showing robustness and improved performance in small samples and non-normal distributions.

Analyzing multisensory integration: dos and donts

The paper argues that behavioral measures of multisensory integration are composite and misinterpreted, proposing a model-based inference pipeline to disentangle underlying factors.

Socio-cognitive models in a patch foraging setting: a case study for model selection and parameter identifiability methods

The paper investigates socio-cognitive mechanisms in collective foraging using agent-based models and evaluates model selection and parameter identifiability through Bayesian inference and Wasserstein distance.

Bayesian inference of global land plant diversification dynamics across the Phanerozoic

This study uses Bayesian methods to analyze land plant diversification dynamics across the Phanerozoic, identifying key patterns and drivers of diversification and extinction.

Empirical-Bayes and Bayesian Hierarchical Modelling forMissingness and Differential Expression in Proteomics

The paper introduces a hierarchical Bayesian model to handle missing data and improve differential expression analysis in proteomics by accounting for uncertainty in missing values.

sandwrm: an R package for estimating Wright's neighborhood size and species-level genetic diversity

The paper introduces an R package called sandwrm to estimate neighborhood size and species-level genetic diversity using a Bayesian approach based on the Wright-Malecot model.

Full-Support Conditional Clade Distribution for Bayesian Tree Topology Testing

This paper introduces KRegCCD, a new Bayesian phylogenetic model that improves posterior tree estimation and enables topology testing by providing full support over tree space.

SFUMATO: Bayesian probabilistic clustering for uncertainty-aware spatialtranscriptomics analysis and mapping

SFUMATO provides a Bayesian probabilistic framework for spatial transcriptomics that captures uncertainty and enables continuous visualization of transcriptional domains.

Fast pace of life is associated with host status in small mammals, despite pervasive surveillance bias

Arenavirus and hantavirus surveillance in small mammals tracks night-lights and accessibility; after adjusting for effort, fast-lived and synanthropic species are somewhat more often detected as hosts.

The prevalence of protein misfolding as a mechanism for hereditary deafness

The paper evaluates computational frameworks to prioritize pathogenic variants in deafness-associated genes, identifying 28,866 VUSs with high pathogenicity probability and improving diagnoses for 12 patients.