Bayesian inference

Natural scene segmentation dynamics reveal iterative Bayesian inference

This study reveals that iterative Bayesian inference explains the spatiotemporal dynamics of natural scene segmentation by integrating visual inputs with spatial priors.

Uncertainty and reward histories have distinct effects on decisions after wins and losses

In 14 rats doing probabilistic reversal learning, model-derived uncertainty (unsigned average prediction error) and recency-weighted reward history distinctly and sex-specifically shaped win-stay versus lose-shift choices.

MCMC-CE: A Novel and Efficient Algorithm for Estimating Small Right-Tail Probabilities of Quadratic Forms with Applications in Genomics

The paper introduces MCMC-CE, an algorithm for estimating small right-tail probabilities of quadratic forms, showing improved accuracy and efficiency in genomics applications.

Major depression and atherosclerotic disease: Linking shared genetics to pathways in blood, brain, heart, and atherosclerotic plaques

This study identifies shared genetic risk between major depression and atherosclerotic diseases and links causal gene expression changes in blood, brain, and heart tissues to depression etiology.

Multi-omics Differential Inference for Functional Interpretation (MoDIFI): A Statistical Framework to Prioritize Cell Lines for Neurodevelopmental Variants

The paper develops MoDIFI, a Bayesian framework to prioritize cell lines and regulatory regions for testing noncoding variants associated with neurodevelopmental disorders.

A network analysis for the identification of gene modules in the transcriptome during Nicotiana benthamiana interfamily grafting

The paper uses Bayesian network analysis to identify gene modules in Nicotiana benthamiana during interfamily grafting, revealing six temporal expression patterns and functional enrichments.

Co-occurring Amino Acid Substitutions Reveal Shared Evolutionary Links between Mammary Gland Location and Litter Size in Mammals

This study links mammary gland location and litter size in mammals through amino acid substitutions, natural selection, and protein networks.

Accurate variant effect estimation in FACS-based deep mutational scanning data with Lilace

Lilace improves variant effect estimation in FACS-based DMS by providing uncertainty quantification and better FDR control.

A Statistical Framework to Infer the Mutation Model of Tandem Repeat Variants

This paper introduces TRAMA, a method to estimate mutation models for tandem repeats using ancestral recombination graphs, showing accurate parameter estimation under SMM and TPM.

Bayesian rhythmic model for jointly detecting circadian biomarkers and predicting molecular circadian time in human post-mortem brain transcriptome

BayCT detects circadian biomarkers and estimates molecular circadian time in human brain transcriptomes, outperforming existing methods by jointly addressing both tasks.

Bayesian data driven modelling of kinetochore dynamics: space-time organisation of the human metaphase plate

The paper uses Bayesian inference to analyze kinetochore dynamics in human cells, identifying spatial and temporal organization patterns during mitosis.

Biomolecular Condensates Dictate the Folding Landscape of Proteins

This study investigates how protein folding landscapes change within biomolecular condensates using atomistic simulations and Bayesian optimization models, revealing sequence-dependent folding behavior influenced by multivalent interactions and crowding.

Causal evidence linking chronic pain genetics to late-onset asthma via the nervous system

The paper identifies a causal link between chronic pain genetics and late-onset asthma through the nervous system using genome-wide association and Mendelian randomization analyses.

Evaluating the Limitations of Bayesian Metabolic Control Analysis

This study evaluates Bayesian Metabolic Control Analysis (BMCA) using synthetic networks, finding it requires flux and enzyme data for accurate predictions and fails to reliably infer elasticity values and allosteric regulation.

Beyond species means - the intraspecific contribution to global wood density variation

Across 109,626 wood density records from 16,829 plant species (GWDD v.2), intraspecific variation explains 15% of global variance, tracks interspecific environmental gradients at 20-30% magnitude, and limits single-plant predictability.

Spike Count Analysis for MultiPlexing Inference (SCAMPI)

The paper introduces an enhanced statistical framework to detect multiplexing in neuronal responses, confirming code juggling occurs on faster timescales and in specific brain regions.

Evolutionary origin and demographic trajectory of tomato spotted wilt virus (Orthotospovirus tomatomaculae)

This study uses Bayesian analysis of TSWV genome sequences to estimate its evolutionary origin, divergence date, and demographic history, finding it originated in South Korea around 1768 CE and expanded with agricultural development.

A Bayesian model for quantifying genomic variant evidence sufficiency in Mendelian disease

The paper introduces a Bayesian model to quantify the sufficiency of genomic variant evidence for Mendelian diseases, enabling consistent interpretation across institutions.

Bayesian BiLO: Bilevel Local Operator Learning for Efficient Uncertainty Quantification of Bayesian PDE Inverse Problems with Low-Rank Adaptation

A normative account of human temporal structure learning

This study develops a Bayesian model of temporal structure learning and shows it aligns with human behavior in predicting outcomes across different temporal environments.

Biological causes and impacts of rugged tree landscapes in phylodynamic inference

This paper investigates the challenges of Bayesian phylodynamic inference due to rugged tree landscapes and proposes diagnostics and strategies to improve analysis reliability.

Genetics-informed bidirectional mapping of glycemic traits and brain phenotypes

This study identifies bidirectional genetic links between glycemic traits and brain phenotypes using Mendelian randomization and validates findings in UK Biobank data.

Quantifying uncertainty in RNA velocity

This paper introduces a Bayesian hierarchical model for RNA velocity estimation with uncertainty quantification, showing improved performance over existing methods in mouse embryonic stem cells.

Cross-View Latent Integration via Nonparametric Gamma Shrinkage Factor Analysis

CLING is a multi-view factor model that improves factor and loading recovery in multi-omic data by using nonparametric Gamma shrinkage, outperforming baselines on synthetic and real datasets.

SpaceBF: Spatial coexpression analysis using Bayesian Fused approaches in spatial omics datasets

SpaceBF identifies spatially varying co-expression patterns in spatial omics data using a Bayesian fused modeling framework, outperforming existing methods in specificity and power.

Risk-averse optimization of genetic circuits under uncertainty

This paper develops a risk-averse optimization framework combining Bayesian inference and Thompson sampling to design robust genetic circuits despite model inaccuracies and parameter uncertainty.

Estimating mosquito bionomics parameters with a hierarchical Bayesian model

The paper estimates bionomic parameters of Anopheles mosquitoes using a hierarchical Bayesian model and quantifies vectorial capacity reduction from insecticide-treated nets.

Bayesian inference captures metabolite-bacteria interactions in a microbial community

The paper develops a Bayesian framework to infer metabolite-bacteria interactions in microbial communities using dynamic network models and time-series data.

Modelling the emergence of spiral colony morphology in the yeast Magnusiomyces magnusii

The paper models spiral colony morphology in yeast using an agent-based model and Bayesian inference to infer hyphal growth parameters.

Accelerating ligand discovery by combining Bayesian optimization with MMGBSA-based binding affinity calculations

The paper combines Bayesian optimization with MMGBSA-based binding affinity calculations to improve ligand discovery by enhancing compound ranking and recovery rates.