Epilepsy Research – Identification of novel drug-targets, using tools of data science
- Epilepsy, a common neurological disease affecting nearly 50 million people across the world. Approximately 10 million people in India. 30% of patients are resistant to the known Anti-Epileptic Drugs (AEDs) There is a need to discover new drugs and drug targets for Epilepsy and to reduce the cost and time for drug discovery computational methods are used.
- In this project, machine learning classifier models are built in-house to identify druggable proteins. A comprehensive Epilepsy database consisting of data related to Anti-epileptic drugs and related gene and drug target information is populated. A platform named TREADS was developed to access in-house developed Machine learning models and Epilepsy Database.
- Search using a Gene Name, Uniprot identifier or the Ensemble Identifier
- Browse – AEDs, AED targets, known Epilepsy-associated genes, epileptic syndromes, and microRNA targets, Epilepsy-associated pathways and protein families.
- Predict potential druggable proteins using machine learning models.
- Epilepsy related PubMed literature is displayed for the proteins of interest.
Chief Investigator Details
Dr. Janaki Ch