Gene–environment interaction: A variable selection perspective
Gene–environment interactions have important implications for elucidating the genetic basis
of complex diseases beyond the joint function of multiple genetic factors and their …
of complex diseases beyond the joint function of multiple genetic factors and their …
[HTML][HTML] Functional Phenotyping: Understanding the Dynamic Response of Plants to Drought Stress
Drought stress, exacerbated by climate change, presents a critical global challenge
characterized by increasingly severe and prolonged drought events. This phenomenon …
characterized by increasingly severe and prolonged drought events. This phenomenon …
Group inverse-gamma gamma shrinkage for sparse linear models with block-correlated regressors
Heavy-tailed continuous shrinkage priors, such as the horseshoe prior, are widely used for
sparse estimation problems. However, there is limited work extending these priors to …
sparse estimation problems. However, there is limited work extending these priors to …
Semiparametric Bayesian variable selection for gene‐environment interactions
Many complex diseases are known to be affected by the interactions between genetic
variants and environmental exposures beyond the main genetic and environmental effects …
variants and environmental exposures beyond the main genetic and environmental effects …
Bayesian longitudinal low-rank regression models for imaging genetic data from longitudinal studies
To perform a joint analysis of multivariate neuroimaging phenotypes and candidate genetic
markers obtained from longitudinal studies, we develop a Bayesian longitudinal low-rank …
markers obtained from longitudinal studies, we develop a Bayesian longitudinal low-rank …
[HTML][HTML] Minimizing the distortions in electrophysiological source imaging of cortical oscillatory activity via Spectral Structured Sparse Bayesian Learning
D Paz-Linares, E Gonzalez-Moreira… - Frontiers in …, 2023 - frontiersin.org
Oscillatory processes at all spatial scales and on all frequencies underpin brain function.
Electrophysiological Source Imaging (ESI) is the data-driven brain imaging modality that …
Electrophysiological Source Imaging (ESI) is the data-driven brain imaging modality that …
[PDF][PDF] Functional physiological phenotyping with functional mapping: A general framework to bridge the phenotype-genotype gap in plant physiology
The recent years have witnessed the emergence of high-throughput phenotyping
techniques. In particular, these techniques can characterize a comprehensive landscape of …
techniques. In particular, these techniques can characterize a comprehensive landscape of …
A Poisson reduced-rank regression model for association mapping in sequencing data
T Fitzgerald, A Jones, BE Engelhardt - BMC bioinformatics, 2022 - Springer
Background Single-cell RNA-sequencing (scRNA-seq) technologies allow for the study of
gene expression in individual cells. Often, it is of interest to understand how transcriptional …
gene expression in individual cells. Often, it is of interest to understand how transcriptional …
Fast algorithms and theory for high-dimensional Bayesian varying coefficient models
Nonparametric varying coefficient (NVC) models are useful for modeling time-varying effects
on responses that are measured repeatedly. In this paper, we introduce the nonparametric …
on responses that are measured repeatedly. In this paper, we introduce the nonparametric …
Computational identification of genes modulating stem height–diameter allometry
The developmental variation in stem height with respect to stem diameter is related to a
broad range of ecological and evolutionary phenomena in trees, but the underlying genetic …
broad range of ecological and evolutionary phenomena in trees, but the underlying genetic …