Bayesian inference

Bayesian bacterial GWAS model reveals threshold-dependent genetic changes in antimicrobial resistance phenotypes

This paper introduces a Bayesian ordered logistic regression GWAS model for bacterial antimicrobial resistance phenotypes, showing improved variant discovery and MIC prediction by accounting for threshold-dependent effects.

Prion Protein Deficiency Results in Synaptic, Neural Network and Behavioral Alterations

Lifelong prion protein (PrP) loss in mice lowers excitatory synaptic proteins, makes network bursts in mature cortical cultures rarer and neuronal activity more correlated, and increases adult dimming-disk escapes.

Do higher-order moments improve inference of population dynamics?

This study shows that using a stochastic model to account for variability in microbial time-series data improves parameter inference compared to deterministic models.

Normative Modeling of Molecular-Enriched Functional Connectivity for Detecting Deviations from Healthy Brain Aging

This paper develops normative models to detect deviations in molecular-enriched functional connectivity associated with amyloid burden in healthy aging brains.

A directed TM->JM coupling in receptor tyrosine kinase dimers, set by activating mutations and the membrane environment

The paper uses MD simulations and computational methods to determine the direction of conformational coupling in RTK dimers, showing it correlates with receptor activity states.

Predictive perception via simultaneous learning and inference

This paper introduces a model that performs exact Bayesian inference over a discrete state space using a local Hebbian rule, demonstrating its ability to account for perception and decision-making under noise.

Estimating conditional cell population associations across tumor density trajectory in three dimensional tissue images

The paper introduces ISPat-3D to estimate conditional cell population associations in 3D tissue images, finding stable associations in colorectal cancer but less stable in breast cancer.

Dissecting shared genetic susceptibility between gastroesophageal reflux disease and psychiatric disorders beyond body mass index

This study identifies shared genetic factors between GERD and psychiatric disorders, showing stronger links with internalizing disorders than with BMI.

HGFX: a validated Python/JAX reproduction of the Hierarchical Gaussian Filter toolbox

The paper presents HGFX, a Python/JAX implementation of the Hierarchical Gaussian Filter that matches a MATLAB reference implementation in behavior and numerical results.

Joint Vector Flow Mapping and Segmentation: Ill-Posedness,Differentiable Bayesian Inference, and Synthetic Vortex-FlowBenchmarks

This paper introduces Bayesian VFM (B-VFM) to address ill-posedness in vector flow mapping by jointly inferring velocity fields, segmentation masks, and uncertainties using Bayesian inference.

Topologically-based parameter inference for agent-based model selection from spatiotemporal cellular data

The paper introduces TOPAZ, a framework that uses topological data analysis and Bayesian methods to infer agent-based models from spatiotemporal cellular data, showing it can accurately recover model parameters and distinguish between models.

New perspectives in assessing environmental risks for birds: a simple TKTD framework to link growth and reproduction energy budget to chemical stress

The paper introduces BIRDkiss, a TKTD framework linking growth and reproduction energy budgets to chemical stress in birds, showing good calibration with observed data and highlighting food availability's role in reproductive outcomes.

FourC: identifying significant and differential contacts in 1D chromatin conformation data

FourC identifies significant and differential contacts in 4C-seq data using a Bayesian model and Gaussian processes to address duplication and model spatial patterns.

A Bayesian framework reveals heterogeneous and stochastic decision-making in NK cell cytotoxicity

This study develops a Bayesian framework to analyze NK cell cytotoxicity and identifies distinct mechanisms underlying variability in killing responses.

TCF25 emerges as a cytoplasmic regulator of GPRASP2 stability

TCF25 is mostly cytoplasmic with a perinuclear membrane-proximal pool, stabilises GPRASP2 against proteasomal degradation, and its C-terminal residues 604-664 are required for their association.

A Bayesian modelling framework for inference of latent infection risk patterns from virus neutralisation assay titration data

The paper introduces a Bayesian framework to infer latent infection risk patterns from virus neutralisation assay titration data, revealing higher and more persistent antibody concentrations for EV-D68 compared to other viruses.

OpenCRS: an open-source regulated human cardiorespiratory model with large-scale calibration and global sensitivity analysis at rest and during exercise

OpenCRS is a cardiorespiratory model calibrated with global sensitivity analysis to identify influential parameters and mechanisms during rest and exercise.

Bayesian Efficient Coding

Letting sensory codes optimize any posterior-based loss makes information maximization (infomax) one special case; blowfly large monopolar cell responses match p = 1/2 Lp reconstruction-error codes better than infomax.

SMORE: joint dimension reduction and cell population discovery on single-cell methylome data

SMORE performs joint dimensionality reduction and cell population discovery on single-cell methylome data, accurately recovering population structures in human datasets.

sabinaMBM: An R package for Multiscale Bayesian species distribution Modelling using INLA

The paper introduces sabinaMBM, an R package for multiscale Bayesian species distribution modeling that improves out-of-sample discrimination and uncertainty propagation across scales.

decemedip: hierarchical Bayesian modeling for cell type deconvolution of immunoprecipitation-based DNA methylomes

The paper introduces decemedip, a Bayesian hierarchical model for cell type deconvolution of MeDIP-seq data, showing its accuracy and utility in identifying methylation signatures.

Inferring the latent network of pairwise mutualistic preferences from observed plant-pollinator interactions

The paper introduces a Bayesian framework to infer latent mutualistic preferences from plant-pollinator visit counts, revealing hidden ecological structure not apparent in raw data.

An open field phenomics resource for multimodal maize yield prediction across divergent environments

Drone imagery from 356 flights in 19 Genomes to Fields maize environments; vegetation-index functional principal components complement genomic kernels, predicting yield of held-out hybrids at r up to 0.501.

Epistasis and an oligogenic architecture underlie the strength of a plant-herbivore interaction

The paper examines how genomic variation in Arabidopsis thaliana affects interaction strength with aphids, finding epistasis among defense genes and an oligogenic architecture.

SmartHisto: Bayesian Active Learning for Histology Images

SmartHisto reduces annotation effort for histopathology images using Bayesian active learning, achieving higher mean IoU than competing methods.

Probabilistic mapping of sub-genic intolerance reveals functional and disease-critical protein regions

PRIME is a Bayesian model that improves estimation of sub-genic intolerance by sharing information across regions, identifying disease-critical protein regions and enhancing variant interpretation.

Estimating protein isoform abundances with PAQu

PAQu estimates protein isoform abundances using multiomic data, outperforming existing methods and revealing increased C4A isoform levels in schizophrenia.

A Unified Neurocomputational Framework for Closed-Loop Motor Control and Sense of Agency

The paper proposes a unified neurocomputational framework linking sense of agency and closed-loop motor control through a Bayesian model of self-causation probability.

OmegaSwitch: Bayesian Markov-Modulated Codon Models for Estimating dN/dS

OmegaSwitch estimates dN/dS ratios across sites and evolutionary lineages using Bayesian Markov-modulated codon models, showing well-calibrated posterior intervals in simulations.

Does Pre-Sensorimotor Brain Activity Modulate TMS-Evoked Potentials?

This study investigates how pre-sensorimotor brain activity affects TMS-evoked potentials during motor imagery, finding that trial-by-trial variability in brain states influences TEP amplitudes.