KC Lab at Michigan Tech
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 sequence, structure, function, and evoltuion. 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 proteome. Additionally, the lab is also focused on prediction of RNA modification site prediction as well as DNA modification site prediction. Another focus in the lab is developing bioinformatics workflows/pipeline to mine information from large amount of next-generation sequencing data. Additionally, the lab is also involved in various collaborative research initiatives in multiple interdisciplinary/convergent research areas.
Recent Updates
- Sep 27, 2022: Our work on prediction of succinylation sites using protien language models has been accepted by Scientific Reports.
- Our work on prediction of S-nitrosylation sites using protin language models has been submitted to GIW/ISCB ASIA 2022.
- Our work on prediction of N-linked glycosylation sites using protin language models has been submitted to Glycobiology.
