Research

Research Areas

 

Precision Medicine

With the advent of high-throughput genomics and advances in computational analytics, precision medicine has emerged as a transformative approach to healthcare. The CCLS members contribute to this field by integrating genomic and clinical data with computational algorithms to develop predictive models for disease risk, prognosis, and treatment response.

Computational Drug Discovery

Computational modeling and simulations have become indispensable tools in drug discovery and development. The CCLS members leverage these techniques to expedite the identification of promising drug candidates, reduce the cost and time required for preclinical testing, and enhance the success rate of clinical trials. Applying computational approaches to virtual screening, molecular docking, and drug optimization enables enable more efficient and targeted drug design, ultimately leading to the development of safer and more effective therapeutics.

Integrative Computational Models

Biological datasets that are derived from DNA, RNA and protein molecules represent the multi-omics datasets (e.g., transcriptomics, epigenomics, proteomics, and genomics). Novel integrative methods to utilize all these omic layers could shed light on the underlying biological mechanism for disease and healthy conditions. The CCLS members develop computational methods to integrate multi-modal biomedical datasets to better characterize the biological processes.