Bayesian inference

Bayesian inference of tissue-migration histories in metastatic cancer from cell-lineage tracing data

This paper introduces BEAM, a Bayesian framework for inferring tissue migration histories in metastatic cancer from lineage tracing data, showing improved performance over existing methods.

A Systems Framework for Quantifying Programmability and Persistence Across Mammalian Cell Types

The paper introduces a Programmability & Persistence Score to evaluate mammalian cell types based on lifespan, engraftment, and resilience, guiding applications in regenerative medicine and immunotherapy.

When the beat drops - The functional anatomy of cardiac-induced sensory attenuation of auditory processing

This paper uses MEG and dynamic causal modelling to show that cardiac systole suppresses auditory deviant responses through local inhibitory gain control, not hierarchical attentional modulation.

Nonlinear Mixed-Effects and Full Bayesian Population Pharmacokinetic Analysis of Ceftolozane-Tazobactam in Critically Ill Patients

This study compares nonlinear mixed-effects and Bayesian hierarchical models for pharmacokinetics of ceftolozane-tazobactam in critically ill patients, showing that Bayesian methods improve parameter consistency with literature when prior information is included.

Testing hypotheses about correlations between brain activation patterns

This paper develops a method to test hypotheses about the correlation between brain activation patterns in fMRI studies, showing that a subject-wise bootstrap on the maximum-likelihood group estimate performs best.

Nonlocal Proliferation and Explosive Tumour Dynamics: Mechanistic Modelling and Bayesian Inference

This paper introduces a mechanistic tumour-growth model with nonlocal feedback and Bayesian inference to explain explosive tumour dynamics and quantify their parameters from data.

Cross-omic dissection reveals locus-specific heterogeneity and antagonistic pleiotropy between Alzheimer's disease and type 2 diabetes

This paper uses cross-omic analyses to show that Alzheimer's disease and type 2 diabetes share some genetic links but also exhibit locus-specific heterogeneity and antagonistic pleiotropy.

Integrating 730,947 exome sequences with clinical literature improves gene discovery

gnomAD v4 (730,947 exomes) brings LOFTEE-2 loss-of-function annotation (0.90 precision, strict mode), missense-aware constraint, and LLM-mined literature evidence combined with constraint to rank disease genes.

Cross-coronavirus host susceptibility loci influence disease severity through immune mediators

The paper identifies immune mediators linking host susceptibility loci to disease severity across SARS-CoV and SARS-CoV-2 infections.

PACMON: Pathway-guided Multi-Omics data integration for interpreting large-scale perturbation screens

PACMON integrates multi-omics data from perturbation screens to infer pathway-level responses to experimental perturbations, achieving high accuracy and scalability.

Structural and contextual biases interact to shape duration perception

The paper quantifies structural and contextual biases in duration perception using a discrimination task and finds that Bayesian inference and rescaling explain the results.

SC-BIG: A Hierarchical Bayesian Model for Bulk-Informed Single Nucleotide Variant Calling in Single Cells

SC-BIG improves single-cell SNV detection by integrating bulk sequencing data, outperforming existing methods in simulated scenarios.

PepCABO: Latent-space Bayesian optimization for peptide-MHC binding using contrastive alignment

PepCABO improves peptide-MHC binding optimization using contrastive alignment and Bayesian optimization in a latent space, outperforming baselines across multiple alleles.

Beyond single-slope Mendelian randomization: structural representation of genetic heterogeneity in joint effect space

This paper introduces MR-UBRA, a Bayesian framework for analyzing genetic heterogeneity in Mendelian randomization, showing it can resolve multi-component structures in causal effect space.

Bayesian inference of gene flow between sister lineages using genomic data

The paper develops a Bayesian method to detect gene flow between sister lineages, showing it has low false-positive rates and high power, and applies it to Sceloporus lizards data.

An alternative patterning mechanism for vertebrate tooth complexity

This study identifies an alternative epithelial patterning mechanism for vertebrate tooth complexity in squamates, showing that cusp formation does not rely on enamel knots but on a broad signaling field.

Unified Multi-Cohort Harmonisation and Normative Modelling of Neuroimaging Data via Hierarchical GAMLSS

This paper introduces a hierarchical GAMLSS framework for harmonizing and modeling neuroimaging data across multiple cohorts, showing improved removal of cohort effects and preservation of biological signals.

BICEP: an extension to indels and copy number variants for rare variant prioritisation in pedigree analysis

BICEP extends its Bayesian model to include indels and copy number variants for rare variant prioritization in pedigrees, showing comparable performance to the original single nucleotide variant model.

NanoVI: a Bayesian variational inference Nextflow pipelinefor species-level taxonomic classification from full-length16S rRNA Nanopore reads

NanoVI provides a Bayesian variational inference pipeline for species-level taxonomic classification of full-length 16S rRNA Nanopore reads, achieving comparable accuracy to Emu with faster execution and fewer false positives.

Joint Bayesian modelling of molecular QTL and GWAS effects improves polygenic prediction for complex traits

Genetically proxied inhibition of angiotensinogen synthesis is associated with lower cardiovascular risk

AGT variants mimicking hepatic angiotensinogen synthesis inhibition are linked, via drug-target Mendelian randomization, to lower coronary artery disease, stroke and heart failure risk and higher potassium.

Network pharmacology-based discovery and experimental validation of novel drug repurposing candidates in Alzheimer's Disease

This paper uses network pharmacology to identify and validate drug repurposing candidates for Alzheimer's Disease, finding arundine and TUDCA as promising candidates.

The Stochastic System Identification Toolkit (SSIT) to model, fit, predict, and design experiments

The paper introduces SSIT, a toolkit for stochastic modeling and analysis, demonstrating its application on yeast and breast cancer datasets.

Neural microstates underlying categorical speech perception using Bayesian nonparametrics

The paper uses Bayesian nonparametrics and machine learning to analyze neural microstates during speech perception, finding that specific microstates and brain regions predict speech categorization accuracy and perceptual gradiency.

An Integrated Population Model to Incorporate Spatio-Temporal Heterogeneity in Demographic Rates

This paper introduces a Bayesian spatially explicit integrated population model to estimate and predict spatio-temporal demographic rates across large geographic areas, showing it provides unbiased and precise estimates even with data misalignment and spatial autocorrelation.

Abiotic Factors and Competitive Exclusion Drive Assembly Patterns in Two Insular Gecko Adaptive Radiations Displaying Ecomorphological Convergence

This study examines two gecko lineages to determine if abiotic factors or competition drive speciation, finding that abiotic factors and competitive exclusion shape phenotypic divergence and convergence.

Genetic liability to hip osteoarthritis confers neurovascular protection against Alzheimer's disease despite depression-mediated phenotypic comorbidity

This study shows genetic liability to hip osteoarthritis protects against Alzheimer's disease through neurovascular mechanisms, but this protection is masked by depression-related comorbidity.

Translational Bayesian Pharmacokinetic Framework for Uncertainty-Aware First-in-Human Dose Selection of Therapeutic Monoclonal Antibodies

This paper develops a Bayesian pharmacokinetic framework to improve uncertainty-aware first-in-human dose selection for monoclonal antibodies by incorporating allometric scaling and population-level variability.

The Phylogeny and the Evolution of Parasitic Strategies in Trematoda

This study reconstructs the evolutionary history of trematode parasitic strategies using mitogenomic and nuclear genomic data, finding that ancestral trematodes had direct life cycles with no intermediate hosts.

The impact of incomplete taxon sampling on inference of gene flow by Bayesian and summary methods using genomic sequence data

This study examines how incomplete taxon sampling affects gene flow inference using genomic data and introduces a Bayesian method to assess gene flow models.