Graph Theoretical and Computational Analysis of Diabetic Disease Network for Identifying New Drug Targets against Diabetes.

Different network parameters like network density, diameter, degree distribution, network heterogeneity, shortest pathlength etc. and topology will be analyzed for better understanding of network structural property. Read More >

Network alignment- A smart and innovative tool for finding structural, functional similarities among species.

The research focus would be on the metabolic networks of Mycobacterium tuberculosis, we would carry out alignment studies of each network of mycobacterium along with networks of related prokaryotes and eukaryotes eventually leading to Homo sapiens. Read More >

Predicting protein functional sites using machine learning approaches.

In this project biological data analysis and processing leading to the development of predictive models for prediction of protein functional sites using machine learning is proposed. Read More >

Predictability of infectious diseases using mathematical modeling.

In this project infectious disease data analysis and processing leading to the development of predictive approaches using the SIR model and its derivatives is proposed. Read More >

Prediction of RNA – RNA interface using Graph theory.

Here we would be representing the RNA secondary structure as a graph, thereby reducing the computational burden of scanning the entire RNA space. Read More >