Jayvee R. Abella

PhD Candidate
in Computer Science

jayvee.r.abella@gmail.com

Rice University

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.

Interests

Structural Bioinformatics
Computational Biophysics
Biomedical Informatics / Data Science / Machine Learning

Education

PhD in Computer Science, 2019
Rice University
MS in Computer Science, 2016
Rice University
BS in Biomedical Engineering, 2014
The University of Texas at Austin

Algorithms for Protein Conformational Sampling

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.

Adaptive Sampling for Simulation of Proteins

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.

Machine Learning on Structural Data

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)

Publications

Jayvee R. Abella, Dinler Antunes, Cecilia Clementi, Lydia Kavraki (2019). APE-Gen: A Fast Method for Generating Ensembles of Bound Peptide-MHC Conformations. Molecules, 24(5).

PDF Code DOI

Dinler Antunes, Jayvee R. Abella, Didier Devaurs, Mauricio Rigo, Lydia Kavraki (2019). Structure-based Methods for Binding Mode and Binding Affinity Prediction for Peptide-MHC Complexes. Current Topics in Medicinal Chemistry 19(5).

DOI

Eugen Hruska, Jayvee R. Abella, Feliks Nuske, Lydia Kavraki, Cecilia Clementi (2018). Quantitative Comparison of Adaptive Sampling Methods for Protein Dynamics. The Journal of Chemical Physics 149(24).

DOI

Didier Devaurs, Malvina Papanastasiou, Dinler Antunes, Jayvee R. Abella, Mark Moll, Daniel Ricklin, John Lambris, Lydia Kavraki (2018). Native state of complement protein C3d analysed via hydrogen exchange and conformational sampling. International Journal of Computational Biology and Drug Design 11(1,2).

DOI

Jayvee R. Abella, Mark Moll, Lydia Kavraki (2018). Maintaining and Enhancing Diversity of Sampled Protein Conformations in Robotics-Inspired Methods. Journal of Computational Biology, 25(1).

DOI

Jayvee R. Abella, Sara Cheng, Qiantao Wang, Wei Yang, Pengyu Ren (2014). Hydration free energy from orthogonal space random walk and polarizable force field. Journal of Chemical Theory and Computation, 10(7).

DOI

Daniel Hensley, Andrew Mark, Jayvee R. Abella, George Netscher, Eugene Wissler, Kenneth Diller (2013). 50 Years of Computer Simulation of the Human Thermoregulatory System. Journal of Biomechanical Engineering, 135(2).

DOI

Teaching

Teaching Assistant for Data Science Courses

Rice University Jul 2019

NLM-GCC Summer Undergraduate Program in Biomedical Informatics (Summer 2019)
K2I Data Science Bootcamp (Summer 2017, Summer 2018)
COMP 440 Artificial Intelligence (Fall 2015, Fall 2016, Fall 2017)
COMP 540 Statistical Machine Learning (Spring 2016, Spring 2017)

Certificate in Teaching and Learning

Rice University Dec 2018

Formal pedagogical training, practical experience, and mentoring to be an effective college teacher

Engineering Tutor

UT Austin Aug 2012 – May 2013

Tutored for core engineering classes such as biology, chemistry, physics, calculus, and programming