Detection and Extraction of Potential Promoter/Enhancer Interactions in Genome of Cancer Patients using an Evolutionary Multi-Objective Algorithm

Cancer, as one of the most common diseases, has influenced the health of many people. The main aim of this study was to present a multi-objective evolutionary algorithm. The algorithm is capable of detecting and extracting potentially promoter/enhancer areas in the chromosomes of the affected people using the information concerning inter-genomic interactions. The correct extraction of these areas can help early diagnosis of cancer.

In this applied and descriptive research, Hi-C data set including information on inter-genomic interactions in the GM12878 cell was used. Multi-objective evolutionary algorithm was used in order to discover and extract potential promoter /enhancer interactions. The mentioned algorithm was implemented using MATLAB software. Furthermore, the efficiency of this algorithm was evaluated using two criteria. The first criterion is a proportional function that calculates the magnitude of inter-genomic interactions relative to the length of the genome regions; and the second criterion is the number of discovered potential promoters/enhancers.

The results and comparisons showed higher efficiency and optimality of the suggested method in discovering promoter/Enhancer interactions with variable length in comparison to HiC-Pro method. Therefore, the suggested method is able to discover the potential promoter/ enhancer interactions that cannot be discovered by HiC-Pro method.

The suggested algorithm is able to optimally discover and extract potential promoter/ enhancer with variable length. This is a great help in medical science for early diagnosis of cancer