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Rapid prototyping of evolution-driven biclustering methods in Julia

Biclustering is a technique of detecting meaningful patterns in tabular data. It is also one of the fields in which evolutionary algorithms have risen to the very top in terms of speed and accuracy. In this short paper we summarize the results of porting one of the leading evolutionary-based biclustering methods EBIC to Julia - an emerging high-end programming language. This is probably the first biclustering package developed in this programming language. The main findings of this study are that flexibility combined with high performance make Julia an appealing platform for development and validation of new biclustering methods.