Bayesian inference

Theoretical and Empirical Performance of Pseudo-likelihood-based Bayesian Inference of Species Trees under the Multispecies Coalescent

This paper evaluates pseudo-likelihood-based Bayesian inference for species tree estimation under the multispecies coalescent, showing theoretical guarantees and empirical performance on synthetic and biological data.

Context modulates brain state dynamics and behavioral responses during narrative comprehension

This study uses fMRI and HMM to show that narrative context modulates brain state dynamics and behavioral responses during story comprehension.

Dynamics-Informed Priors (DIP) for Neural Mass Modelling

This paper introduces DIP-DCM, a method that improves parameter estimation in neural mass models by using dynamics-informed priors, showing better performance in predicting neuroimaging data and capturing disease mechanisms.

Modelling Discrete States and Long-Term Dynamics in Functional Brain Networks

This paper introduces DyNeStE, a model that combines recurrent neural networks with Bayesian inference to capture long-term dynamics in brain networks while maintaining interpretability, outperforming HMMs in simulations and resting-state MEG data.

Multiscale Parcellation of Dynamic Causal Models of the Brain

This paper introduces a multiscale parcellation method for dynamic causal models of the brain, showing scale invariance in empirical causal networks.

Real-time Bayesian optimization of deep brain stimulation for personalized cognitive control enhancement

This study uses Bayesian Optimization to find optimal DBS parameters in rats for improving cognitive control, showing consistent effects across acute and chronic settings.

BASCULE: Bayesian inference and clustering of mutational signatures leveraging biological priors

BASCULE uses a Bayesian framework to standardize and cluster mutational signatures across cancer types, identifying prognostic subtypes in over 8,000 samples.

The Algorithm for Reversible Jump Inference of Motifs

This paper introduces TARJIM, a method that infers sequence motifs from DNA-protein binding data by using reversible jump Metropolis Hastings to determine both the number and sequence of motifs.

Did you see the sound? A Bayesian Perspective on Crossmodal Perception in Low Vision

The paper investigates crossmodal perception in low vision and finds that auditory-driven illusions depend on local visual reliability rather than global enhancement.

Identification of Potential targets for Stroke and Its Subtypes by Integrating Proteomes and Genetics from Human Plasma

This study identifies seven plasma protein-associated genes linked to stroke and its subtypes using multi-omics integration and MR analysis, with six showing causal relationships.

Uncovering Multi-Omics Profiles of Population Heterogeneity: A Cluster-Based Bayesian Approach

MOCHA identifies latent population subgroups with distinct genetic effects from multi-omics data, revealing two neurodevelopmental clusters linked to adolescent inhibitory control.

Best Practices for Modeling Arthropod Lifetimes in a Bayesian Framework

This study evaluates how data distribution and transformations affect Bayesian inference of thermal performance curves for arthropod lifespans using simulated data.

MIRAGE: a Bayesian rare variant association analysis method incorporating functional information of variants

MIRAGE improves rare variant association analysis by incorporating variant functional information, outperforming existing methods in simulations and autism exome-sequencing data.

STbayes: An R package for creating, fitting and understanding Bayesian models of social transmission

The paper introduces an R package called STbayes for Bayesian analysis of social transmission using network-based diffusion models, demonstrating its ability to distinguish individual and social learning contributions.

Diversification dynamics of the Palaeozoic actinopterygian radiation

Birth-death-sampling models of Palaeozoic ray-finned fish occurrences detect no origination increase after the Hangenberg event; cryptic Late Devonian diversification and survival likely explain Carboniferous diversity gains.

Semi-supervised Bayesian integration of multiple spatial proteomics datasets

This paper introduces a semi-supervised Bayesian method to integrate spatial proteomics data with other omic datasets to improve protein subcellular localization inference.

EEG Reveals Robust Within-Person but Unstable Between-Person Neural Encoding of Pain

This study uses EEG to show that within-person pain encoding is stable across time and cohorts, while between-person differences are less consistent.

Unified Probabilistic Analysis of CyTOF: A Deep Generative Approach using CytoOne

CytoOne is a probabilistic framework for CyTOF data that integrates batch correction, differential analysis, and visualization, effectively modeling sparse and noisy data.

Neural mechanisms of flexible perceptual inference

This study investigates how mice adapt to changing contexts through perceptual inference, showing that adaptation is driven by internal belief updates rather than reward feedback.

Evaluating the causal effect of mitochondrial dysfunction on Alzheimer's and Parkinson's disease using Polygenic Risk Scores and Mendelian Randomization

This paper uses Polygenic Risk Scores and Mendelian Randomization to evaluate the causal effect of mitochondrial DNA copy number on Alzheimer's and Parkinson's disease risk.

Evaluating selection at intermediate scales within genes provides robust identification of genes under positive selection in M. tuberculosis clinical isolates

The paper evaluates positive selection in M. tuberculosis genes at three scales, finding that intermediate-scale analysis identifies the most credible candidate genes under selection.

S4-Multi: enhancing polygenic score prediction in ancestrally diverse populations

S4-Multi improves polygenic score prediction across diverse ancestries by reducing genetic variants while maintaining accuracy in non-European populations.

Inflammatory profiles of transdiagnostic symptom dimensions in healthy females

This study links transdiagnostic symptom dimensions in healthy females to specific inflammatory profiles using Bayesian regression and PCA, showing associations between social withdrawal and monocyte counts, and anxious-depression with stress-induced inflammation.

Bayesian inference of population structure using identity-by-descent-based stochastic block models

This paper introduces a Bayesian framework for inferring population structure using IBD-based stochastic block models, showing improved accuracy over heuristic methods in both simulated and real data.

mfSuSiE enables multi-cell-type fine-mapping and multi-omic integration of chromatin accessibility QTLs in aging brain.

mfSuSiE improves fine-mapping of chromatin accessibility QTLs across multiple cell types and integrates multi-omic data in aging human brain samples.

Single-cell phylodynamics reveal rapid late-stage colorectal cancer expansions

The paper uses single-cell whole-genome sequencing and Bayesian phylodynamic modeling to show colorectal tumors often originate decades before diagnosis and expand rapidly in the last two years.

Reconciling time and prediction error theories of associative learning

This paper proposes a Bayesian theory for temporal causal learning that explains learning phenomena through timescale invariance and integrates aspects of timing and prediction error theories.

Hierarchical Bayesian modeling of multi-region brain cell count data

The paper applies hierarchical Bayesian modeling to multi-region brain cell count data, showing improved inference over traditional methods in under-sampled datasets.

Deep White-Matter Pathways Mediate the Link Between Docosahexaenoic Acid (DHA) Status and Cognitive Performance in Adolescence

The paper identifies a deep white-matter pathway linking DHA status to cognitive performance in adolescents using multimodal MRI and Bayesian modeling.

Bayesian model-averaging of parametric coalescent models for phylodynamic inference

This paper introduces a Bayesian Model Averaging framework for phylodynamic inference that integrates multiple coalescent models to better capture demographic histories without pre-specifying a single model.