Abstract
Genetic Engineering being one of the latest area of research findings still left much to be desired in practice. Genetic Engineering is the method of changing the inherited characteristics of an organism in a predetermined way by altering its genetic materials. This is often done to cause micro-organisms, such as bacteria and viruses, to synthesize increased yields of compounds, to form entirely new compounds or to adapt to different environments. This paper attempts to proffer heuristic algorithm (a neural networks model that can learn from experience) as an approach to the study of Gene Therapy in Genetic Engineering. Neural Networks models computational capabilities are more effective at performing information processing operations, the likes that occur in Genetic Engineering. Given a threshold of number of connections between a set of simple neurons, a form of self-organization takes place just as in predicting or increasing yields of compounds, or in gene therapy which is the supply of a functional gene to person with a genetic disorder.