Finding semantic patterns in omics data using concept rule learning with an ontology-based refinement operator.

ABSTRACT:

Background

Identification of non-trivial and meaningful patterns in omics data is one of the most important biological tasks. The patterns help to better understand biological systems and interpret experimental outcomes. A well-established method serving to explain such biological data is Gene Set Enrichment Analysis. However, this type of analysis is restricted to a specific type of evaluation. Abstracting from details, the analyst provides a sorted list of genes and ontological annotations of the individual genes; the method outputs a subset of ontological terms enriched in the gene list. Here, in contrary to enrichment analysis, we introduce a new tool/framework that allows for the induction of more complex patterns of 2-dimensional binary omics data. This extension allows to di

SUBMITTER: Malinka F 

PROVIDER: S-EPMC7466824 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature