Bayesian inference

Seven replicated genomic associations of myalgic encephalomyelitis/chronic fatigue syndrome: a biobank study

Targeted-learning GWAS of 1,268 UK Biobank ME/CFS cases found 176 FDR-significant variants; seven replicated in disjoint UK Biobank or All of Us cohorts.

Two-State Effective Connectivity Predicts the Effect of Anterior Cingulate Cortex Excitatory / Inhibitory Balance on Posterior Cingulate Cortex

The paper develops a network-level measure combining MRI spectroscopy ratios and effective connectivity to show that Glx/GABA ratio shapes posterior cingulate cortex connectivity.

Scalable context-dependent single-cell eQTL mapping reveals disease-relevant regulatory variation beyond static models

The paper introduces CASTIE, a method for context-dependent eQTL mapping in single-cell data, identifying regulatory variants missed by static models and linking them to disease traits.

Towards reconstruction of the human interactome from positive and negative experimental evidence

Inferring tested-but-undetected pairs from prey lists of 5,530 published interaction screens yields 97 million tested human protein pairs and 18,982,508 non-interactions (≥3 tests) for calibrating screens and predictors.

Dissociable changes in temporal precision and causal expectations following perceptual training

Simultaneity-judgment training reduced flash-illusion susceptibility similarly in children with and without ADHD; Bayesian modelling showed lower common-cause prior in typical children versus lower temporal uncertainty in ADHD.

Calibrating Classifiers Across Covariates: Hierarchical Vocal Density Estimation for Acoustic Monitoring at Scale

This paper develops a Bayesian hierarchical calibration method for acoustic classifiers to estimate site-level vocal density with uncertainty, improving accuracy and efficiency over global or site-specific approaches.

Disentangling the Relationship Between Mind Wandering and Symptom Dimensions in a Non-Clinical Sample: The Key Link with ADHD

The paper examines the relationship between mind wandering and seven symptom dimensions in a non-clinical sample, finding that ADHD symptoms uniquely predict mind wandering after accounting for shared variance.

Mammalian spermatogenesis at single-cell resolution downstream of genetic perturbations in meiotic double-strand break repair

Single-nucleus RNA+ATAC profiling of 32 mice shows asymmetric PRDM9 binding drives asynapsis, pachytene cell loss, aneuploidy and multi-megabase crossover redistribution, tuned by a chromosome 15 locus.

Vascular waveform analysis using Bayesian pulse deconvolution

This paper introduces Bayesian pulse deconvolution to improve vascular waveform analysis by jointly solving signal filtering, pulse timing detection, and pulse shape extraction, achieving significant error reductions in simulations and real-world data.

Holocene North Asian gene flow and cryptic substructure in the genome history of Nilgiri tribes

This study analyzes the genomic history of Nilgiri tribes, revealing fine-scale substructure and complex Holocene gene flow patterns.

Activity-level evaluation of DNA transfer to stockings: comparisonof HaloGen with simplified contributor-based approaches

This paper evaluates DNA transfer to stockings using HaloGen, showing its ability to distinguish active contact from social contact, while simplified methods lose important information.

Shared genetic architecture between brain iron deposition and Alzheimer's disease

This study identifies shared genetic factors between brain iron deposition and Alzheimer's disease, revealing a polygenic basis and potential neuroimmune mechanisms.

Bayesian Inference of Gene Regulatory Networks at Stochastic Steady State

This paper introduces a Bayesian method for inferring gene regulatory networks using a Chemical Langevin Equation model, enabling structure identification and kinetic parameter estimation without observing transient dynamics.

Macroevolutionary Rates of Species Interactions: Approximate Bayesian Inference from Cophylogenies

This paper introduces an ABC method to infer speciation rates in cophylogenetic systems, finding host speciation is the fastest in a beetle-mimic commensalism dataset.

FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies

FM-GPT is a Bayesian fine mapping method that identifies causal genes in phenome-wide transcriptome-wide association studies, improving accuracy and reducing false positives.

SCG: Spatially Co-Expressed Gene Identification through Spatially Varying Networks

This paper introduces SCR, a Bayesian framework for estimating spatially-resolved gene co-expression networks to identify spatially co-expressed genes as potential biomarkers and therapeutic targets.

Causal roles of phenotypic age and metabolic health on dementia: a Mendelian randomisation and structure learning study

This study uses Mendelian randomisation and causal network analysis to evaluate the causal effects of phenotypic age acceleration and metabolic health on dementia, finding no evidence of a causal effect but identifying key biomarkers.

Modeling Patient-Reported Pain Trajectories with Frequent Minimum and Maximum Scores

The paper introduces a Bayesian beta-binomial mixed-effects model to analyze zero- and one-inflated patient-reported pain scores, showing improved fit and accuracy compared to existing methods.

A hierarchical Bayesian framework accommodates intraspecific and interspecific variation in multivariate traits

The paper introduces a hierarchical Bayesian framework to estimate taxon-specific intraspecific covariance structures and evolutionary processes for multivariate traits, showing improved uniformity in evolutionary rate estimates across the great ape clade.

GLORB: Robust Bayesian inference for differential expression underglobal expression shifts

GLORB improves differential expression analysis by accounting for global expression shifts, outperforming existing methods in scenarios with widespread upregulation or downregulation.

INFORME: coupling information-theoretic experimental design with nonlinear mixed-effects modeling for efficient observation scheduling

INFORME uses information-theoretic design with mixed-effects modeling to adaptively schedule measurements, reducing the number of scans needed for patient-specific treatment response prediction.

BARCS: beta-binomial regression for multivariate CRISPR screen design

BARCS extends beta-binomial regression to handle complex CRISPR screen designs, showing improved essential gene recovery but calibration issues in gene-level summaries.

HiCPotts: An R/Bioconductor package to identify significant interactions in chromosome conformation capture data and model sources of biases.

HiCPotts is an R/Bioconductor package that identifies significant chromatin interactions in Hi-C data while modeling biases using a zero-inflated Negative Binomial distribution.

Bayesian adaptive experimental design for efficient microbial genome-wide association studies

This paper introduces BASS-GWAS, a Bayesian method for efficient microbial GWAS, identifying causal loci with fewer phenotyped isolates than random sampling.

Synchronizing speciation, extinction, and dispersal to island paleodynamics through Bayesian phylogenetics in a Hawaiian plant radiation

The paper introduces a Bayesian phylogenetic framework to infer divergence times, ancestral ranges, and diversification rates in Hawaiian plants without fossil calibration.

FlexiTAC enables controllable PROTAC linker generation across diverse structural settings using a Bayesian flow network with posterior guidance

FlexiTAC generates controllable PROTAC linkers using a Bayesian flow network, improving validity and pose quality over existing methods.

Efficient capture-recapture inference for spatially varying natal dispersal,survival and recruitment

This paper introduces an efficient Bayesian model for estimating natal dispersal and spatially varying demographic parameters using capture-recapture data, applied to white stork populations across 101 spatial units.

A Bayesian Multi-Species Approach Infers Gene Regulatory Networks Across Non-Model Organisms

This paper introduces GRN-BMuSeR, a Bayesian multi-species method for gene regulatory network inference, showing improved performance in bacteria and novel predictions in archaea.

Inference of self-limiting neutrophil swarming dynamics using Bayesian physics-informed neural networks

The paper develops a Bayesian physics-informed neural network to model neutrophil swarming dynamics in human and murine cells, revealing species-specific differences in recruitment and self-limitation.

Transcriptomic and proteomic Mendelian randomization identifies putative therapeutic targets for thoracic aortic disease

This study uses Mendelian randomization to identify 28 putative causal genes for thoracic aortic disease, highlighting potential therapeutic targets.