NOVEL APPROACH FOR DRUG DISCOVERY USING NEURAL NETWORK BACK PROPAGATION ALGORITHM by Neha Tandon
A complex structure that focuses on the analysis of variety of levels in regular manner is known as the ontology process. It is different from the methods that evaluate the ontology in a direct manner. When there is a need to transcendently automate the evaluation and not totally leaving the work on clients is the main focus here. There has been an involvement in the programmed learning methods for constructing the ontology which is completely a level-based method. There are different strategies included for various levels. There are all these levels that are defined at various levels. The hominidae species is represented as base class in the ontology method. Here the class, object properties as well as data properties are present. There are three classes further present which are gene, Go_id and the gene functionality. For the purpose of mapping the two base classes, the object properties are utilized. Basically it involves the five different properties that are belongs_to, has_go, has_gene, has_evidence, and has_functionality. In this work, technique is been proposed which is based on the neural networks which will mark the area for which the drug need to be discovered. The proposed technique is implemented in MATLAB and it is been analyzed that accuracy is increased and execution time is reduced.