Main Category
Applied Analytics
Name
CACONET
URL
https://github.com/yuanwxu/corr-net-classify
Description
CACONET is a computational framework that can be used to distinguish between "diseased" and "healthy" microbial correlation networks inferred from relative abundance data. It can also be used to identify potential signature interactions characteristic of the networks, offering possible targets for further biological and clinical research. CACONET consists of an inference component for compositional-aware correlation inference, a classification component for the classification of the correlation networks, and an explanation component for extraction of signature interactions from the classifier.
Keywords
-microbial correlation network
-relative abundance data
Other Categories
Applied Analytics
Main Category
Applied Analytics
Name
CACONET
URL
https://github.com/yuanwxu/corr-net-classify
Description
CACONET is a computational framework that can be used to distinguish between "diseased" and "healthy" microbial correlation networks inferred from relative abundance data. It can also be used to identify potential signature interactions characteristic of the networks, offering possible targets for further biological and clinical research. CACONET consists of an inference component for compositional-aware correlation inference, a classification component for the classification of the correlation networks, and an explanation component for extraction of signature interactions from the classifier.
Keywords
-microbial correlation network
-relative abundance data
Other Categories
Applied Analytics