10 citations · 10 across the 6 of their papers we have counts for
6 papers
Supervised Integrative Biclustering with applications to Alzheimer's Disease
Kaifeng Yang, Thierry Chekouo, Sandra E. Safo
Multiple types or views of data (e.g. genetics, proteomics) measured on the same set of individuals are now popularly generated in many biomedical studies. A particular interest mi…
A Bayesian Integrative Mixed Modeling Framework for Analysis of the Adolescent Brain and Cognitive Development Study
Aidan Neher, Apostolos Stamenos, Mark Fiecas +2
Integrating high-dimensional, heterogeneous data from multi-site cohort studies with complex hierarchical structures poses significant feature selection and prediction challenges.…
Broken Adaptive Ridge Method for Variable Selection in Generalized Partly Linear Models with Application to the Coronary Artery Disease Data
Christian Chan, Xiaotian Dai, Thierry Chekouo +2
Motivated by the CATHGEN data, we develop a new statistical learning method for simultaneous variable selection and parameter estimation under the context of generalized partly lin…
Bayesian variable selection using an informed reversible jump in imaging genetics: an application to schizophrenia
Djidenou Montcho, Daiane Zuanetti, Thierry Chekouo +1
From a practical perspective, proposals are one of the main bottleneck for any Markov Chain Monte Carlo (MCMC) algorithm. This paper suggests a novel data driven or informed propos…
Bayesian Integrative Analysis and Prediction with Application to Atherosclerosis Cardiovascular Disease
Thierry Chekouo, Sandra E. Safo
Cardiovascular diseases (CVD), including atherosclerosis CVD (ASCVD), are multifactorial diseases that present a major economic and social burden worldwide. Tremendous efforts have…
The Gibbs-plaid biclustering model
Thierry Chekouo, Alejandro Murua, Wolfgang Raffelsberger
We propose and develop a Bayesian plaid model for biclustering that accounts for the prior dependency between genes (and/or conditions) through a stochastic relational graph. This…