Optimal ranking and directional signature classification using the integral strategy of multi-objective optimization-based association rule mining of multi-omics data.

ABSTRACT: Introduction: Association rule mining (ARM) is a powerful tool for exploring the informative relationships among multiple items (genes) in any dataset. The main problem of ARM is that it generates many rules containing different rule-informative values, which becomes a challenge for the user to choose the effective rules. In addition, few works have been performed on the integration of multiple biological datasets and variable cutoff values in ARM. Methods: To solve all these problems, in this article, we developed a novel framework MOOVARM (multi-objective optimized variable cutoff-based association rule mining) for multi-omics profiles. Results: In this regard, we identified the positive ideal solution (PIS), which maximized the profit and minimized the

SUBMITTER: Mallik S 

PROVIDER: S-EPMC10415913 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature