A comparative study of association rules for mining gene expression databases : a brief survey

Abstract EN

Mining gene expression datasets became an important bioinformatics research problem.

Many mining techniques have been proposed to analyze these data such as clustering, and association rules techniques.

Due to the nature of gene expression dataset, association rules algorithms are more suitable to analyze such data than other mining techniques.

This paper presents a brief survey of different association rules algorithms that have been proposed for gene expression dataset.

It demonstrates the merits, practicality, and limitations of their use.