Developing and Applying Computational Algorithms to Reveal Health-Related Biomolecular Interactions
Computational biology is an interdisciplinary area that applies computational approaches in biological big data, including protein amino acid sequences, genetic sequences, etc., which is widely used to analyze protein-protein interactions, make predictions in drug discovery, develop vaccines, etc. Popular methods include mathematical modeling, molecular dynamics simulations, data science mythology, etc. With the help of computational algorithms and applications, drug development is much faster than traditional processes, as it reduces risks early on in a drug discovery process and helps researchers select target candidates that have the highest potential for success. In my doctoral research, I applied multi-scale computational approaches to health-related biomolecules including coronaviruses, UDG enzyme in DNA repair mechanisms, microtubule proteins, etc. My studies involved MD simulations, biological data science, machine learning algorithms, etc., which demonstrate a new understanding of those health-related biomolecules.
Xie, Yixin, "Developing and Applying Computational Algorithms to Reveal Health-Related Biomolecular Interactions" (2022). ETD Collection for University of Texas, El Paso. AAI29209111.