Jayvee Abella is a PhD student in Computer Science at Rice University. His advisors are Prof. Lydia Kavraki and Prof. Cecilia Clementi. His work focuses mainly on the computational modeling, simulation, and analysis of proteins and their structure and dynamics. Jayvee’s passion lies in providing informatics and data science solutions to biomedical problems.
PhD in Computer Science, 2019
MS in Computer Science, 2016
BS in Biomedical Engineering, 2014
The University of Texas at Austin
I have developed algorithms, inspired from the field of robot motion planning, to successfully model low-energy conformations of protein and protein-ligand systems in a scalable manner.
Sampling rare events with Molecular Dynamics can be accelerated with adaptive sampling methods, which use machine learning to automatically determine a bias that can speed up the exploration of the simulation. I have experience with the analysis of these methods, and I am currently applying them to study peptide binding with MHCs.
I am currently developing a deep Convolutional Neural Network to predict binding affinity of peptide-MHC complexes based on structures produced from APE-Gen. In collaboration with Daniel Bao (University of Houston). Feature image credits: Aphex34 (Wikimedia Commons)