Our research interest lies in the area of computational data science with applications to bioinformatics, computational biology, health informatics, etc. Among others, our lab is focused on developing computational tools to decipher relationships between protein sequences, structures, functions, and evolutions. Currently, the lab is developing machine learning and deep learning based approaches to characterize protein post-translational modification that are known to be the main drivers of increasing the diversity of the proteome. Additionally, the lab is also focused on the prediction of RNA and DNA modification sites. Another focus in the lab is developing bioinformatics workflows/pipeline to mine information from large amounts of next-generation sequencing data. Additionally, the lab is also involved in various collaborative research initiatives in multiple interdisciplinary/convergent research areas.