Background

• Ph.D. Biomedical Sciences, College of Medicine, University of South Alabama, Mobile, AL, 2012
• Postdoc, Computational Biology group, Louisiana State University, Baton Rouge, LA, 2012-2014
• Postdoc, Center for Computation and Technology, Louisiana State University, Baton Rouge, LA, 2013-2014

Expertise

• Computational biology, bioinformatics.
• Drug design, protein structure modeling, ligand binding site identification and molecular docking.
• Serial & parallel programming and troubleshooting.

Publications

• Fang Y, Ding Y, Feinstein WP, Koppelman DM, Moreno J, Jarrell M, Ramanujam J, Brylinski M. 2016. GeauxDock: Accelerating structure-based virtual screening with heterogeneous computing. PLoS ONE. 11(7):e0158898
• Feinstein WP, Brylinski M. 2016. Structure-based drig doscpveru accelerated by many-core devices. Curr Drug Targets 17(14):1595-1609
• Ding Y, Fang Y, Feinstein WP, Ramanujam J, Koppelman DM, Moreno J, Brylinski M, Jarrell M. 2015. GeauxDock: A novel approach for mixed-resolution ligand docking using a descriptor-based force field. J Comput Chem. 36(27):2013-2026
• Feinstein WP, Brylinski M. 2015. Accelerated structural bioinformatics for drug discovery. High Performance Parallelism Pearls. 2:55-72
• Feinstein WP, Brylinski M. 2015. Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets. J Cheminform
• Feinstein WP, Moreno J, Jarrell M, Brylinski M. 2015. Accelerating the pace of protein functional annotation with Intel Xeon Phi coprocessors. IEEE Trans Nanobioscience. 14(4):429-439
• Ragothaman A, Boddu SC, Kim N, Feinstein WP, Brylinski M, Jha S, Kim J. 2014. Developing eThread pipeline using SAGA-Pilot abstraction for large-scale structural bioinformatics. Biomed Res Int. 2014:348725
• Feinstein WP, Brylinski M. 2014. eFindSite: Enhanced fingerprint-based virtual screening against predicted ligand binding sites in protein models. Mol Inform. 33(2):135-50
• Brylinski M, Feinstein WP. 2013. eFindSite: Improved prediction of ligand binding sites in protein models using meta-threading, machine learning and auxiliary ligands. J Comput Aided Mol Des. 27(6):551-567
• Brylinski M, Feinstein WP. 2012. Setting up a meta-threading pipeline for high-throughput structural bioinformatics: eThread software distribution, walkthrough and resource profiling. J Comput Sci Syst Biol. 6(1):001-010

Background

• Ph.D. Biomedical Sciences, College of Medicine, University of South Alabama, Mobile, AL, 2012
• Postdoc, Computational Biology group, Louisiana State University, Baton Rouge, LA, 2012-2014
• Postdoc, Center for Computation and Technolog, Louisiana State University, Baton Rouge, LA, 2013-2014

Computational biology, bioinformatics.

Drug design, protein structure modeling, ligand binding site identification and molecular docking.

Serial & parallel programming and troubleshooting.