ShinyBN: an online application for interactive Bayesian network inference and visualization.

ABSTRACT:

Background

High-throughput technologies have brought tremendous changes to biological domains, and the resulting high-dimensional data has also posed enormous challenges to computational science. A Bayesian network is a probabilistic graphical model represented by a directed acyclic graph, which provides concise semantics to describe the relationship between entities and has an independence assumption that is suitable for sparse omics data. Bayesian networks have been broadly used in biomedical research fields, including disease risk assessment and prognostic prediction. However, the inference and visualization of Bayesian networks are unfriendly to the users lacking programming skills.

Results

We developed an R/Shiny application, shinyBN, which is an online graphical user i

SUBMITTER: Chen J 

PROVIDER: S-EPMC6916222 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature