The scourge of infectious diseases is one of the problems contending with humanity. All infectious diseases are caused by pathogens. A major problem in biological research is the creation of enormous and redundant amounts of genomic data. From this large volume of generated data, biologists select a subset of each sequence known as DNA nucleotide subsequences "words", for extended scientific analysis. Computational biology aids this pruning process by providing computerized tools to generate vital information with biological significance from these data. This research aimed to develop new tools for extracting DNA repeats from the gene sequences and also to perform a comparative analysis with existing tools having similar or closely-related functions. We were able to develop BengaSaVex (GBenga Samuel Victor genetic sequence extraction tool) and provide a sequential in-silico geneticsequence-filtering functionality to identify repeated DNA nucleotide subsequences within the genes of some microorganisms, evaluated the potential benefits and applications of identifying such repeated sequences, and finally, performed an in-silico comparative analysis between BengaSaVex and tandem repeat finder.