Bayesian inference

hibayes: An R Package to Fit Individual-Level, Summary-Level and Single-Step Bayesian Regression Models for Genomic Prediction and Genome-Wide Association Studies

hibayes provides an R package for fitting Bayesian regression models in genomic prediction and GWAS, supporting individual-level, summary-level, and single-step approaches.

Individual patterns of functional connectivity in neonates as revealed by surface-based Bayesian modeling

This study uses a Bayesian framework on fMRI data to estimate individual functional connectivity patterns in neonates, revealing age-related changes and individual variability.

Linking microscopy to diffusion MRI with degenerate biophysical models: an application of the Bayesian EstimatioN of CHange (BENCH) framework

The paper applies the BENCH framework to link diffusion MRI signal changes to microstructural features in brain tissue using histology data.

Bayesian automatic screening of pneumoniaand lung lesions localization from CT scans. Acombined method toward a more user-centredand explainable approach

This paper develops a Bayesian method for pneumonia and lung lesion localization in CT scans, combining uncertainty measures with object detection to improve explainability and reduce automation bias.

Bayesian Aggregation of Multiple Annotations Enhances Rare Variant Association Testing

BayesRVAT improves rare variant association testing by integrating multiple annotations, increasing power and detecting novel gene-disease associations in real data.

iComBat: An Incremental Framework for Batch Effect Correction in DNA Methylation Array Data

The paper introduces an incremental batch effect correction framework for DNA methylation data, allowing new data to be corrected without reprocessing existing data.

Bayesian Workflow for Generative Modeling in Computational Psychiatry

The paper applies Bayesian workflow to improve parameter and model identifiability in hierarchical Bayesian models using multivariate behavioural data from a reward learning task.

Precise calcium-to-spike inference using biophysical generative models

The paper develops biophysically-inspired models to improve spike inference from calcium imaging by accounting for kinetic features of fluorescent indicators.

The winner's curse under dependence: repairing empirical Bayes using convoluted densities

The paper addresses the winners curse in statistical estimation under dependence, proposing a density convolution method to improve empirical Bayes approaches and demonstrating its effectiveness through simulations and a real-world application.

Evaluation of Bayesian Linear Regression Derived Gene Set Test Methods

This paper evaluates Bayesian Linear Regression derived gene set tests, showing they outperform MAGMA in detecting genetic associations with complex diseases.

The use of variational autoencoders to characterise the heterogeneous subpopulations that arise due to antibiotic treatment

This study uses a Bayesian Variational Autoencoder to analyze bacterial single-cell RNA sequencing data and identify subpopulations responding to antibiotic treatment.

Phylogenetic relatedness rather than aquatic habitat fosters horizontal transfer of transposable elements in animals

The paper analyzes horizontal transfer of transposable elements in 247 animal species, finding that phylogenetic relatedness, not aquatic habitat, strongly influences HTT rates.

Opioid use disorder and brain health: observational andgenetic associations

This paper investigates the causal impact of opioid use disorder on brain health outcomes using observational and genetic analyses, finding increased dementia risk associated with both OUD diagnoses and genetic predisposition to OUD.

Sequential design of single-cell experiments to identify discrete stochastic models for gene expression.

This paper develops a sequential experiment design strategy to efficiently identify discrete stochastic models for gene expression using single-cell data.

Echidna: A Bayesian framework for quantifying gene dosage effect impacting phenotypic plasticity

Echidna quantifies gene dosage effects on phenotypic plasticity by integrating scRNA-seq and WGS data to separate genetic from cell non-autonomous mechanisms.

A hierarchical Bayesian brain parcellation framework for fusion of functional imaging datasets

This paper introduces a hierarchical Bayesian framework that fuses task-based and resting-state neuro-imaging datasets to create a population-based atlas of the human cerebellum, achieving better individual parcellations with limited data.

Leveraging functional annotations to map rare variants associated with Alzheimer's disease with gruyere

This study introduces gruyere, a Bayesian model that improves rare variant association analysis by integrating functional annotations, identifying 15 new AD-associated genetic associations.

Bayesian Perspective for Orientation Determination in Cryo-EM with Application to Structural Heterogeneity Analysis

This paper introduces a Bayesian framework for orientation estimation in cryo-EM, showing it improves reconstruction accuracy and structural heterogeneity analysis.

DoRIAT: A Bayesian Framework For Interpreting And Annotating TCR-pHLA Docking Runs.

DoRIAT improves docking run interpretation by selecting models close to native structures, achieving top 10 rankings in 80% of cases using RMSD.

PsiPartition: Improved Site Partitioning for Genomic Data by Parameterized Sorting Indices and Bayesian Optimization

PsiPartition improves genomic data partitioning using parameterized sorting indices and Bayesian optimization, outperforming existing methods on simulated and empirical datasets.

Bayesian Least-Squares Supertrees (BLeSS): flexible inference of large time-calibrated phylogenies

BLeSS infers time-calibrated phylogenies from multiple time trees, producing posterior distributions of topologies and divergence times across large datasets.

Bayesian Mendelian Randomization Analysis for Latent Exposures Leveraging GWAS Summary Statistics for Traits Co-Regulated by the Exposures

This paper introduces a Bayesian Mendelian randomization framework to analyze causal effects of latent exposures on disease outcomes using GWAS summary statistics for co-regulated traits.

De novo identification of protein domains in cryo-electron tomography maps from AlphaFold2 models

DomainSeeker identifies protein domains in cryo-ET maps using AlphaFold2 structures and Bayesian inference, improving accuracy and resolution robustness.

Association of Body Index with Fecal Microbiome in Children Cohorts with Ethnic-Geographic Factor Interaction: Accurately Using a Bayesian Zero-inflated Negative Binomial Regression Model

The paper introduces a Bayesian zero-inflated negative binomial regression model to analyze microbiome data in children cohorts, revealing insights into microbial abundance and covariate effects.

Bayesian Hierarchical Hypothesis Testing in Large-Scale Genome-Wide Association Analysis

This paper introduces a Bayesian Hierarchical Hypothesis Testing method for GWAS that improves power and fine-mapping resolution, leading to more discoveries in serum urate risk variant mapping.

Population Performance and Individual Agreement of Coronary Artery Disease Polygenic Risk Scores

This study evaluates the reliability of coronary artery disease polygenic risk scores across diverse populations, finding poor individual agreement despite equivalent population-level performance.

Bayesian Causal Inference Accounts for Multisensory Filling-In at the Blind Spot

The paper investigates multisensory perception at the blind spot using a Bayesian Causal Inference model, finding preserved integration and flexible parameter adaptation.

Sparse matrix factorization robust to sample sharing across GWAS reveals interpretable genetic components

This paper introduces GLEANR, a method for sparse matrix factorization of GWAS summary statistics that accounts for sample sharing and identifies interpretable genetic factors.

Deciphering Memory Patterns in Eco-Epidemiological systems through the lens of BaFOMS: A Bayesian Fractional Order Model Selection Method

This paper introduces BaFOMS, a Bayesian method for selecting fractional order models to analyze eco-epidemiological systems, demonstrating its effectiveness in parameter estimation and forecasting.

Highly Accurate Non-Invasive Preimplantation Genetic Testing for Monogenic and Polygenic Diseases from Spent Medium

This paper presents a non-invasive preimplantation genetic testing method using spent embryo culture medium, achieving high accuracy for monogenic and polygenic disease detection without modifying IVF workflows.