Bayesian inference

Single-Cell Transcriptome-Wide Mendelian Randomization and Colocalization Analysis Reveals Immune Cell-Specific Mechanisms in Alzheimer's Disease

This paper uses single-cell eQTL-MR and colocalization analysis to identify immune cell-specific genetic mechanisms associated with Alzheimer's disease risk.

Bayesian phylogenetic inference accounting for recombination in whole bacterial genomes

This paper introduces ClonalFrame2, a Bayesian method for phylogenetic inference in bacteria that accounts for recombination, showing improved accuracy in simulated and real datasets.

The behaviour bends, the code holds: working-memory category information in the multiple-demand network across graded interruption

This study investigates how the multiple-demand network maintains working memory during task interruptions, finding that neural representations of category information remain stable despite behavioral costs.

Ecology of gene drives: Organism fitness under larval competition determines gene drive performance

This study investigates how larval competition affects gene drive performance in Aedes aegypti mosquitoes using agent-based models and Bayesian optimization.

A single day of natural daylight exposure and physical activity does not conclusively change circadian phase: A Bayesian crossover experiment

This study investigates the effects of natural daylight and physical activity on circadian phase using a Bayesian crossover experiment, finding inconclusive results.

The Segmentome: a novel representation of the DNA methylome identified by a Bayesian HMM framework

The paper introduces the segmentome, a DNA methylome representation using a Bayesian HMM, and shows it can group cell types and identify cell-of-origin in DNA samples.

A generative network model reveals hierarchical structural memory guiding post-mitotic 3D genome inheritance

The paper introduces HiCONA, a Bayesian framework that identifies mitotically preserved chromatin interactions guiding post-mitotic 3D genome reassembly and epigenetic memory.

Phylogeny-Guided Global-Local Shrinkage for Microbiome Feature Selection

This paper introduces PGL, a Bayesian regression method for microbiome feature selection that uses phylogenetic trees to improve detection of exposure-associated ASVs.

Unravelling genomic and environmental contributions to nitrogen-use efficiency in tropical maize through Bayesian causal forests

This paper uses Bayesian causal forests to estimate the causal effect of nitrogen levels on maize traits, finding that environmental factors largely drive trait variation while genomic background influences baseline levels.

Defective Viral Genomes Reveal History-dependent Self-regulation of Type I Interferon Dynamics

The paper develops a Bayesian model to show that defective viral genomes modulate type I interferon dynamics by both inducing and suppressing IFN through cumulative exposure, explaining how pandemic viruses evade innate immunity.

Soft Sensing of Intracellular States for CHO Cell Bioprocessing with Ensemble Kalman Filters

This paper uses Ensemble Kalman Filters to estimate intracellular nucleotide sugar donors in CHO cell cultures from extracellular measurements, improving metabolic state inference.

Plasma Proteogenomics Identifies RGMB as a Candidate for Primary Open-Angle Glaucoma Detected Only in East Asians

The paper identifies RGMB as a potential risk factor for East Asian POAG through proteogenomic analysis, showing ancestry-specific associations and lack of colocalization with IOP traits.

Inferring the multi-host fitness landscape of endive necrotic mosaic virus from cross-inoculation experiments

The paper infers a multi-host fitness landscape of endive necrotic mosaic virus using cross-inoculation experiments and a Bayesian model linked to Fisher's geometrical model.

Fixing the Measurement Model Before the Selection Heuristics: Optimiser Repairs for Living-Cell Self-Driving Laboratories

This paper compares measurement-aware models and selection-level repairs in Bayesian optimisation for living-cell experiments, finding that measurement-aware models reduce regret and improve coverage under data contamination.

Bayesian in situ point spread function modeling enables high-fidelity three-dimensional nanoscopy in deep tissue

This paper introduces Bayesian in situ PSF modeling to improve 3D nanoscopy in deep tissue by accounting for optical distortions and uncertainties in PSF estimation.

Single-cell transcriptome-wide Mendelian randomization and colocalization analyses reveal immune-cell-specific mechanisms and actionable drug targets in prostate cancer

The paper identifies immune-cell-specific genetic associations and drug targets in prostate cancer using integrative analyses of single-cell and bulk data.

Climate-associated genomic variation across life stages reveals population-specific signals of local adaptation in European beech

The paper identifies climate-associated genomic variation in European beech across life stages, revealing population-specific adaptive responses to temperature and precipitation changes.

SPARK: Bayesian structure learning of enhancer-based gene regulatory networks from single-cell multiomics data and prior knowledge

SPARK reconstructs enhancer-based gene regulatory networks using single-cell multiomics data and prior knowledge, revealing regulatory links associated with immune disease GWAS variants.

Structural Determinants of the Energetic Barrier of Phospholipid Flip-Flop

The paper calculates flip-flop free-energy barriers for over 700 membrane-lipid combinations using Martini 3 simulations and develops a Bayesian model to predict barriers based on chemical descriptors and membrane structure.

Bayesian Stacking of Quantitative Adverse Outcome Pathways Isolates Primary Drivers of Liver Steatosis

This paper develops a Bayesian framework to integrate multiple converging pathways in adverse outcome pathways, demonstrating improved predictive performance for liver steatosis.

pyreml: a general-purpose, GPU-accelerated mixed model solver in Python

pyreml is a GPU-accelerated Python library for linear mixed models that outperforms existing closed-source REML software in speed and functionality.

A clinically annotated proteomic and histological resource of 1,000 colorectal cancers

Deep proteomics of 997 treatment-naïve colorectal cancers defines six subgroups, splitting chromosomally unstable tumors into three and revealing a rare adverse subgroup, with H&E slide benchmarks.

Scalable phylodynamic inference of mutational and epistatic fitness effects with multi-feature birth-death models

This paper develops a Bayesian framework for inferring mutational and epistatic fitness effects in microbial evolution using multi-feature birth-death models and applies it to Escherichia coli phylogenies.

Described eukaryotic species in published species-level phylogenies: placement by molecular data, dates and date uncertainty

The paper analyzes published eukaryotic phylogenies to assess molecular placement, dating, and uncertainty across species groups.

LynchRisk: a Bayesian network to estimate the probability of Lynch syndrome based on pedigree and tumor characteristics

LynchRisk estimates Lynch syndrome probability using pedigree, cancer history, and tumor MMR status through a Bayesian model.

CascadeMAP: Autonomous Closed-loop Optimization of Enzyme Cascades via Microfluidics, Machine Learning and Agentic AI

Unattended droplet-microfluidic Bayesian optimization of a glycerol detection cascade matched design of experiments (DoE) with one third of the conditions; a second cascade used DoE with Raman readout.

Bayesian Variable Selection Approaches to Identifying Selection in Evolutionary Datasets

This paper introduces a Bayesian variable selection method for identifying selection in phylogenetic datasets, showing it outperforms Dirichlet-process models and avoids phantom selection artifacts.

Climate-driven fitness decline in Japanese Chum Salmon reshapes North Pacific salmon biogeography, with reproductive consequences: A Bayesian network analysis

The paper uses Bayesian networks to show climate-driven fitness decline in Japanese Chum Salmon affects reproductive traits and reshapes salmon biogeography.

Simulation-free approximate Bayesian computation for stochastic reaction networks

This paper introduces SFABC, a simulation-free method for Bayesian inference of stochastic reaction networks, showing it matches simulation-based accuracy at lower computational cost.

abcneuralnet: Simulation-based Inference with Bayesian Neural Networks and Explainable AI for Population Genomics Inference

abcneuralnet provides a Bayesian Neural Network framework with explainable AI for population genomics inference, offering calibrated prediction intervals and uncertainty decomposition.