8 citations · 24 across the 14 of their papers we have counts for
4 papers · 1 filter
CMiNet: R package for learning the Consensus Microbiome Network
Rosa Aghdam, Claudia Solis-Lemus
Understanding complex interactions within microbiomes is essential for exploring their roles in health and disease. However, constructing reliable microbiome networks often poses a…
Identifying microbial drivers in biological phenotypes with a Bayesian Network Regression model
Samuel Ozminkowski, Claudia Solis-Lemus
1. In Bayesian Network Regression models, networks are considered the predictors of continuous responses. These models have been successfully used in brain research to identify reg…
CARlasso: An R package for the estimation of sparse microbial networks with predictors
Yunyi Shen, Claudia Solis-Lemus
Microbiome data analyses require statistical tools that can simultaneously decode microbes' reactions to the environment and interactions among microbes. We introduce CARlasso, the…
Bayesian Chain Graph LASSO Models to Learn Sparse Microbial Networks with Predictors
Yunyi Shen, Claudia Solis-Lemus
Microbiome data require statistical models that can simultaneously decode microbes' reaction to the environment and interactions among microbes. While a multiresponse linear regres…