Bayesian inference

Causal inference for multiple risk factors and diseases from genomics data

The paper introduces CI-GWAS, a method to improve causal inference in GWAS by addressing confounding and pleiotropy, finding few suitable IVs and replicating some but not all previously reported causal links.

North American bird occupancy dynamics attributed to climate and land use change

This study attributes changes in North American bird occupancy to climate and land use change using counterfactual simulations and Bayesian models, finding climate change negatively affected 90% of species and land use change 96%.

Extracellular matrix regulates lineage plasticity in prostate cancer through YAP/TEAD

Loss of extracellular matrix-integrin signaling switches off YAP/TEAD and lets prostate adenocarcinoma organoids turn neuroendocrine; LATS inhibition reverses it, and combined YAP, NOTCH and AR inhibition fully reprograms them.

Atomic modeling of radiation damage in cryoelectron microscopy datasets

This paper develops a Bayesian framework to model radiation damage in cryo-EM datasets by inferring atomic displacements and structural changes during electron irradiation.

PROBE: A Neurophysiology-Informed Bayesian Optimization Framework for Adaptive TMS Motor Hotspot Mapping, Algorithm Design and Monte Carlo Evaluation

The paper introduces PROBE, a Bayesian optimization framework for TMS motor hotspot mapping, showing improved accuracy and efficiency compared to grid search and other methods.

Genomic analysis identifies polygenic and region-specific contributions to ADHD-migraine comorbidity

This study identifies shared genetic variants and gene expression mechanisms between ADHD and migraine using genome-wide association data and multiple genetic analyses.

MOFTy: Multimodal Gaussian Process Factor Analysis with Numerical Information Field Theory

MOFTy disentangles spatial structures and recovers cross-modal patterns in multi-omics data by separating smooth gradients from fine-scale heterogeneity.

Bayesian model discovery for reverse-engineering biochemical networks from data

This paper introduces a Bayesian sparse likelihood-free inference method to reverse-engineer biochemical networks from single-cell data, showing high accuracy and outperforming correlation-based methods.

Ultra-deep duplex sequencing reveals unique features of somatic evolution in the normal tissues of a family with Li-Fraumeni syndrome

Duplex sequencing of a Li-Fraumeni family links germline TP53 p.R181H to higher neutral-region mutagenesis and weaker blood TP53 selection, plus recurrent p.R248Q/W hits across proband tissues.

Genetically nominated cardiovascular-kidney-metabolic features are not consistently more responsive to weight-loss and cardiometabolic interventions

This study shows that molecular features genetically linked to cardiovascular-kidney-metabolic diseases do not consistently show greater response to weight-loss and cardiometabolic interventions compared to other features.

Minimally invasive monitoring of clonal evolution through integrated single cell and ctDNA analysis

cfClone, a Bayesian model, deconvolves cfDNA whole-genome sequencing using scWGS-derived haplotype-specific clone copy-number profiles to estimate tumour fraction, clonal prevalence, and flag missed clones.

Representation in genetic studies affects inference about genetic architecture

Across UK Biobank, All of Us and FinnGen, the inferred mean direction (sign bias) of rare minor-allele effects varies and is largely explained by each cohort's trait skewness.

Seeing Through Touch: Visual Reliability Shapes Tactile Guidance in 360° Virtual Reality

This study investigates how visual and tactile cues are combined in 360° virtual reality, finding that degraded vision increases reliance on tactile guidance and alters multisensory integration.

BayesForge: A Bayesian Inference library for Python, R, and Julia

BayesForge provides a unified Bayesian inference framework across Python, R, and Julia, enabling high-performance computation with hardware acceleration and demonstrating significant speedups over existing methods.

Benchmarking Bayesian colocalization methods in validating Mendelian randomization-identified targets

This study benchmarks four Bayesian colocalization methods to validate MR-identified protein-trait associations for cardiometabolic traits, finding SharePro most frequently supports significant associations.

Behavioral metabolic suppression confounds thermal performance estimates and climate vulnerability assessments in a marine ectotherm

In an undescribed intertidal Urticina anemone, heat-induced closure suppresses measured respiration, and fitted thermal performance curves place the critical thermal maximum far above the 25-30°C lethal range.

Bats decouple sonar gaze from steering to resolve sensory conflict

The paper studies how bats resolve sensory conflict by decoupling sonar gaze from steering and introduces a Bayesian framework for modeling this behavior.

Menstrual cycle phase length variation is associated with daily symptom burden

This study shows that menstrual phase length variation is linked to daily symptom intensity, highlighting the need for individualized baseline assessments rather than fixed phase assumptions.

Phylogenetic network reconstruction reveals reassortment signatures at segment and genotype levels in human Rotavirus A

This study uses Bayesian phylogenetic networks to analyze reassortment patterns in human Rotavirus A segments, finding changes in reassortment rates and genotype compatibility over time.

STR-PG: A Topology-decoupled Pangenome Framework for Scalable Short-read Genotyping of Short Tandem Repeats

STR-PG provides a scalable framework for short-read STR genotyping by decoupling locus representation from allele content, reducing computational costs while maintaining accuracy.

Evolution of multicellularity and reproductive strategies in yellow-green algae (Xanthophyceae, Heterokontophyta)

This study reconstructs the evolution of multicellularity and reproductive strategies in Xanthophyceae using phylogenomic data, showing multiple transitions to multicellularity linked to changes in propagule types.

Harmonizing Peak Matching Between Multidimensional NMR Spectra

This paper develops an algorithm to automate cross-peak matching between multidimensional NMR spectra by modeling deviations as a distribution of noise and true shifts, using Bayesian inference to provide confidence estimates.

Coevolution-informed Bayesian optimization for sample-efficient protein design

This paper introduces ALSEBO, a Bayesian optimization method for protein design that efficiently finds optimal sequences with few evaluations by leveraging coevolutionary statistics.

Evolution-inspired multi-objective Bayesian optimization for protein engineering

This paper introduces EvoMOBO, a multi-objective Bayesian optimization framework for protein engineering, showing improved performance in enzyme tasks compared to wild-type variants.

Simulation-based Bayesian deep learning enables uncertainty-aware tumor fraction estimation in cell-free DNA

This paper introduces purNPE, a Bayesian deep learning framework for estimating tumor fraction in cell-free DNA without labeled cancer samples, achieving comparable performance to existing methods.

SpinForecast: chain-free probabilistic backbone assignment of intrinsically disordered proteins from NMR chemical shifts

SpinForecast assigns residue-specific chemical shifts to disordered proteins without sequential chain building, achieving high accuracy in peak assignment for three test proteins.

Resource depletion accelerates rate learning but not composition learning in patch foraging

This paper develops a Bayesian model of foraging in a patchy environment, showing resource depletion accelerates rate learning but not composition learning.

The extrinsic incubation period for Zika virus: a Bayesian time delay modelling study

This paper estimates the temperature-dependent extrinsic incubation period (EIP) for Zika virus using Bayesian models, finding non-linear declines in EIP with increasing temperature and longer EIPs in Ae. albopictus than Ae. aegypti.

Statistical factorization in motor control: Opposing biases from statistics on different timescales enable fast and accurate behavior

The paper shows that motor control uses two statistical processes on different timescales to improve both speed and accuracy of movements.

Uncertainty-aware breeding decisions: MCMC-based optimum contribution selection increases breeding decision robustness

The paper introduces CVaR-OCS, a method that improves breeding decisions by incorporating uncertainty in genetic evaluations, leading to more robust selection outcomes.