Bayesian inference

CBKMR: A Copula-based Bayesian Kernel Machine Regression Framework for Optimal Marker Detection in Omics Data

CBKMR improves marker detection in omics data by capturing nonlinear gene-outcome relationships and interactions, outperforming existing methods in accuracy and uncertainty quantification.

Modeling Psychophysical Data in R: A Comparative Study of Four Model Frameworks

The paper compares four model frameworks in R for analyzing psychophysical data, focusing on two-level and hierarchical approaches for group-level inference.

Reliable estimates of Japanese encephalitis virus evolutionary rate supported by a formal test of temporal signal

This study estimates the evolutionary rate of Japanese encephalitis virus using Bayesian analysis and identifies discrepancies in previous estimates by assessing temporal signal.

Incorporating continuous characters in joint estimation of dicynodont phylogeny

This study estimates dicynodont phylogeny using continuous traits under Brownian motion models and finds they contribute different signal compared to discrete traits, leading to different tree topologies.

Chromosome Size as a Robust Predictor of Recombination Rate: Insights from Holocentric and Monocentric Systems

The paper identifies chromosome number and mean chromosome size as proxies for recombination rate using genetic map data from 73 insect species and 157 monocentric plants, showing mean size is a better predictor, especially in holocentric species.

Multi-ancestry proteogenomic analysis identifies risk proteins for intracranial aneurysms

This paper identifies risk proteins for intracranial aneurysms using multi-ancestry proteogenomic analysis and finds ADH4 and PLEKHA1 as non-blood pressure-mediated candidates.

Circadian timing does not modulate human temporal contrast sensitivity

This study investigates whether circadian timing affects human temporal contrast sensitivity and finds no evidence of circadian modulation in cone-mediated visual performance.

A Bayesian Neural Ordinary Differential Equations Framework to Study the Effects of Chemical Mixtures on Survival

The paper introduces a Bayesian neural ODE framework to predict the effects of chemical mixtures on survival, showing improved modeling of complex interactions in toxicology.

Block-structured Bayesian source estimation model for magnetoencephalography signals

This study introduces a block-structured Bayesian model for MEG source estimation that integrates functional brain areas and inter-areal relationships, improving accuracy in localizing neural activity.

Inferring the causes of animal social network structure from time-series data

This paper introduces a causal Bayesian framework to infer the causes of animal social network structure from continuous-time focal-animal sampling data.

Bayesian multilevel modeling of group and participant level effect sizes: Stronger inter-individual differences in pupil dilation compared to EEG alpha power during aversive conditioning

This study compares pupil dilation and EEG alpha power during aversive conditioning, finding greater inter-individual variability in pupil dilation effects at the participant level.

Gene module-trait network analysis uncovers cell type specific systems and genes relevant to Alzheimers Disease

The paper identifies cell type-specific gene modules associated with Alzheimer's Disease traits using snRNASeq data from human brain tissues.

Shedding light on Amazonian phylogeographic patterns and evolutionary history of night monkeys (Genus: Aotus) using reconstructed fecal metagenomic shotgun sequencing

This study uses fecal metagenomic sequencing to refine the phylogenetic classification and evolutionary history of Aotus night monkeys, revealing three main clades and clarifying species boundaries.

Fine-mapping methods for complex traits: essential adaptations for samples of related individuals

This paper introduces Bayesian fine-mapping methods adapted for related individuals, showing improved accuracy in pig data compared to existing tools.

Failure to meet the exchangeability assumption in Bayesian multispecies occupancy models: Implications for study design

This paper shows that violating the exchangeability assumption in multispecies occupancy models can reduce statistical power and lead to worse inference than single-species models, especially with limited sampling.

Topographic variation in neurotransmitter receptor densities explains differences in intracranial EEG spectra

This paper shows that incorporating neurotransmitter receptor densities improves biophysically informed models of intracranial EEG spectra, linking molecular characteristics to cortical population dynamics.

Detection dog performance state estimation from pre-stimulus video and physiological signals using deep learning and Bayesian inference

This paper develops a deep learning and Bayesian framework to estimate detection dog performance states from pre-stimulus video and physiological signals, identifying missed alerts with 85% detection and 81% precision.

Natural variation in regulatory code revealed through Bayesian analysis of plant pan-genomes and pan-transcriptomes

The paper introduces K-PROB, a Bayesian method to identify cis-regulatory elements in plant pan-genomes by linking sequence variation with gene expression.

GRASS-NB: Group-structured variable selection for spatial negative binomial data with applications to cancer registry and spatial omics

The paper introduces a Bayesian negative binomial regression model with group-structured priors for spatially correlated count data, applied to cancer registry and spatial omics datasets.

Bayesian Cooperative Learning for Multimodal Integration

This paper introduces BayesCOOP, a Bayesian method for multimodal integration that avoids MCMC and variational approaches, showing improved performance in estimation and uncertainty assessment.

TyCHE enables time-resolved lineage tracing of heterogeneously-evolving populations

TyCHE improves time-resolved lineage tracing by accounting for heterogeneous mutation rates, applied to memory B cells, germinal centers, gliomas, and bacterial infections.

Comparative phylogeography of lizards (Squamata: Phrynosomatidae) in Baja California and expansion of Callisaurus draconoides within the North American deserts

The paper examines the phylogeography of lizards in Baja California, identifying divergence events and range expansions, particularly in Callisaurus draconoides.

Generation of virtual populations for quantitative systems pharmacology through advanced sampling methods

This paper evaluates DREAM(ZS) for generating virtual populations in QSP, showing it outperforms Metropolis-Hastings in parameter space exploration and correlation preservation.

Modeling asymmetric Thermal Performance Curves for proportion data

This paper introduces the LINEX Thermal Performance Curve, a novel non-linear model for asymmetric thermal responses, and demonstrates its superior fit for biological traits using simulations and experimental data.

Sparse Polygenic Risk Score Inference with the Spike-and-Slab LASSO

This paper introduces SSLPRS, a Polygenic Risk Score method using Spike-and-Slab LASSO, showing improved variable selection and prediction accuracy over existing methods.

Systems modeling and uncertainty quantification of AMP-activated protein kinase signaling

The paper develops a data-informed model of AMPK signaling using uncertainty quantification and biosensors, showing AMPK integrates inputs over time during exercise.

Hydroplane I: one-shot probabilistic evolutionary analysis for scalable organizational identification.

Hydroplane introduces a fast Bayesian method for metagenomic evolutionary analysis, demonstrating effectiveness in detecting homologs and estimating lineage diversity using kmer data.

Antagonistic histone post-translational modifications improve the fidelity of epigenetic inheritance - a Bayesian perspective

The paper models how antagonistic histone PTMs improve epigenetic inheritance fidelity using Bayesian methods and simulations.

Global Footprint of the Multidrug Resistance Island Ec17R and Resistance Gene Co-Occurrence in Pathogenic Escherichia coli Isolates

The paper tracks a multidrug-resistant E. coli lineage over years, identifies a globally distributed resistance island, and finds resistance gene co-occurrence networks and antibiotic tolerance in isolates lacking known resistance mechanisms.

LimROTS: A Hybrid Method Integrating Empirical Bayes and Reproducibility-Optimized Statistics for Robust Differential Expression Analysis

LimROTS improves differential expression analysis in proteomics by combining empirical Bayes and reproducibility-optimized statistics for better accuracy and reproducibility.