Cross-validation for training and testing co-occurrence network inference algorithms.

ABSTRACT:

Background

Microorganisms are found in almost every environment, including soil, water, air and inside other organisms, such as animals and plants. While some microorganisms cause diseases, most of them help in biological processes such as decomposition, fermentation and nutrient cycling. Much research has been conducted on the study of microbial communities in various environments and how their interactions and relationships can provide insight into various diseases. Co-occurrence network inference algorithms help us understand the complex associations of micro-organisms, especially bacteria. Existing network inference algorithms employ techniques such as correlation, regularized linear regression, and conditional dependence, which have different hyper-parameters that determine th

SUBMITTER: Agyapong D 

PROVIDER: S-EPMC11883995 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature