Data- and expert-driven rule induction and filtering framework for functional interpretation and description of gene sets.

ABSTRACT:

Background

High-throughput methods in molecular biology provided researchers with abundance of experimental data that need to be interpreted in order to understand the experimental results. Manual methods of functional gene/protein group interpretation are expensive and time-consuming; therefore, there is a need to develop new efficient data mining methods and bioinformatics tools that could support the expert in the process of functional analysis of experimental results.

Results

In this study, we propose a comprehensive framework for the induction of logical rules in the form of combinations of Gene Ontology (GO) terms for functional interpretation of gene sets. Within the framework, we present four approaches: the fully automated method of rule induction without filtering,

SUBMITTER: Gruca A 

PROVIDER: S-EPMC5483958 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature