Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[OSS]: CACONET #48

Open
hollydawnmurray opened this issue Mar 28, 2022 · 0 comments
Open

[OSS]: CACONET #48

hollydawnmurray opened this issue Mar 28, 2022 · 0 comments
Assignees
Labels
submitted Good for newcomers

Comments

@hollydawnmurray
Copy link

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

@hollydawnmurray hollydawnmurray added the submitted Good for newcomers label Mar 28, 2022
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
submitted Good for newcomers
Projects
None yet
Development

No branches or pull requests

2 participants