Genetic Disease Identification and Medical Diagnosis using MF, CC, Bp, Microrna and Transcription Factors

There are a lot of upcoming and new evolving diseases that the humans cannot predict. These diseases are found and analysed in the last stages and feel helpless in saving the humans. If we could determine the disease and predict in the early stages, human lives can be saved much more than we can imagine. So Genomic and Proteomic Dataset (GPD) is created, which integrates the most relevant sources of bio information. This dataset helps the user to find their genetic diseases that they obtained from their families in advance. The hospitals can make use of these data to keep track on their patient’s health. Cross ontology is used to evaluate the gene test values from three ontologies for determining the genetic disease. We compare the cellular component, molecular function and biological process values between the input values and the average values. If any two of the input values are greater than the normal genetic values then the person is prone to extrinsic diseases or else intrinsic diseases. The diseases obtained as the result of cross ontology is integrated with the miRNA – transcription factor interactive diseases using the fusion technique. Disease updation is used to optimize the diseases from the above interactions and update the diseases whenever new diseases are encountered. Tree Representation gives us the complete structure of genetic diseases identified by various process, their symptoms and cure for the particular diseases to the associated user.