DescriptionComputers are aiding biotechnology researchers to rapidly develop new engineered strains of organisms with favorable product accumulation. The organisms being engineered can be represented as constraint based metabolic models. These models are analyzed using computational methods to find optimal genetic manipulation strategies such as gene knockouts. Due to growing biological knowledge, there has been a corresponding increase in the size and complexity of the $in>silico$ metabolic models. Therefore the biotechnology research community needs access to an effective computational method and an efficient implementation of the method that reasonably quickly solves the problem of searching for genetic manipulations. Furthermore, the biotechnology researchers are of diverse backgrounds and their computer skills are different. This should not hinder the community from using these computational techniques. In order to address the above requirements, an efficient and user-friendly software solution has been proposed and developed for discovering strategies that may enhance the yield of chemical compounds of interest.