Biclustering-of-Expression-Data-using-Evolutionary-Computing

It is the implementation of this paper

The approach is based on evolutionary algorithms, which have been proven to have excellent performance on complex problems, and searches for biclusters following a sequential covering strategy. The goal is to find biclusters of maximum size with mean squared residue lower than a given threshold over gene-expression data. In addition, more attention is paid to the fact of looking for high-quality biclusters with large variation, i.e., with a relatively high row variance, and with a low level of overlapping among biclusters.