A toolbox of machine learning software to support microbiome analysis.

ABSTRACT: The human microbiome has become an area of intense research due to its potential impact on human health. However, the analysis and interpretation of this data have proven to be challenging due to its complexity and high dimensionality. Machine learning (ML) algorithms can process vast amounts of data to uncover informative patterns and relationships within the data, even with limited prior knowledge. Therefore, there has been a rapid growth in the development of software specifically designed for the analysis and interpretation of microbiome data using ML techniques. These software incorporate a wide range of ML algorithms for clustering, classification, regression, or feature selection, to identify microbial patterns and relationships within the data and generate predictive models. This r

SUBMITTER: Marcos-Zambrano LJ 

PROVIDER: S-EPMC10704913 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature