Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean

A Rairdin, F Fotouhi, J Zhang, DS Mueller… - Frontiers in plant …, 2022 - frontiersin.org
Using a reliable and accurate method to phenotype disease incidence and severity is
essential to unravel the complex genetic architecture of disease resistance in plants, and to …

Dissecting the genetic architecture of leaf morphology traits in mungbean (Vigna radiata (L.) Wizcek) using genome‐wide association study

KO Chiteri, S Chiranjeevi, TZ Jubery… - The Plant Phenome …, 2023 - Wiley Online Library
Abstract Mungbean (Vigna radiata (L.) Wizcek) is an important pulse crop, increasingly used
as a source of protein, fiber, low fat, carbohydrates, minerals, and bioactive compounds in …

Dissecting the root phenotypic and genotypic variability of the Iowa mung bean diversity panel

KO Chiteri, TZ Jubery, S Dutta… - Frontiers in Plant …, 2022 - frontiersin.org
Mung bean [Vigna radiata (L.) Wilczek] is a drought-tolerant, short-duration crop, and a rich
source of protein and other valuable minerals, vitamins, and antioxidants. The main …

A geometric approach to informed MCMC sampling

V Roy - arXiv preprint arXiv:2406.09010, 2024 - arxiv.org
A Riemannian geometric framework for Markov chain Monte Carlo (MCMC) is developed
where using the Fisher-Rao metric on the manifold of probability density functions (pdfs) …

Bayesian iterative screening in ultra-high dimensional settings

R Wang, S Dutta, V Roy - arXiv preprint arXiv:2107.10175, 2021 - arxiv.org
Variable selection in ultra-high dimensional linear regression is often preceded by a
screening step to significantly reduce the dimension. Here a Bayesian variable screening …

Two-Step Mixed-Type Multivariate Bayesian Sparse Variable Selection with Shrinkage Priors

SH Wang, R Bai, HH Huang - arXiv preprint arXiv:2201.12839, 2022 - arxiv.org
We introduce a Bayesian framework for mixed-type multivariate regression using continuous
shrinkage priors. Our framework enables joint analysis of mixed continuous and discrete …

New Variational and Sampling Algorithms for Large-scale Bayesian Model Selection Problems

G Li - 2022 - oaktrust.library.tamu.edu
Significant progress has been achieved in computer inference for Bayesian models during
the past few decades. There has been continuous improvement in a wide variety of …

Bayesian Variable Selection Under High-dimensional Settings With Grouped Covariates

P Agarwal, S Dutta, M Mukhopadhyay - arXiv preprint arXiv:1609.06031, 2016 - arxiv.org
Consider the normal linear regression setup when the number of covariates p is much larger
than the sample size n, and the covariates form correlated groups. The response variable y …

[引用][C] BRAVO: AN R PACKAGE FOR PERFORMING BAYESIAN VARIABLE SELECTION WITH EMBEDDED SCREENING FOR ULTRA-HIGH DIMENSIONAL …

D Li, S Dutta, V Roy - Bayesian variable selection in ultra-high …, 2021 - Iowa State University