Published in Nature Communications, 2024
Characterizing protein dynamics in the crystalline state
Recommended citation: Klyshko E, Kim JS-H, McGough L, Valeeva V, Lee E, Ranganathan R, Rauscher S (2024) "Functional protein dynamics in a crystal." Nature Communications 15(1):3244
Published in BMC Bioinformatics, 2023
A computer vision tool to detect baker yeast colonies
Recommended citation: Christopher J Nunn, Eugene Klyshko, Sid Goyal (2023). "petiteFinder: An automated computer vision tool to compute Petite colony frequencies in bakers yeast." BMC Bioinformatics 24, 50.
Published in Biophysical Journal, 2022
Computational method to track ordered water in simulations
Recommended citation: E Klyshko, JSH Kim, S Rauscher (2022). "LAWS: Local Alignment for Water Sites — tracking ordered water in simulations." Biophysical Journal. 122 (14), 2871-2883
Published in Computational and Structural Biotechnology Journal, 2022
The paper describing a computational model of microtubule dynamics
Recommended citation: Evgenii Kliuchnikov, Eugene Klyshko, Maria S. Kelly, Artem Zhmurov, Ruxandra I. Dima, Kenneth A. Marx, Valeri Barsegov (2022). "Microtubule assembly and disassembly dynamics model: Exploring dynamic instability and identifying features of Microtubules’ Growth, Catastrophe, Shortening, and Rescue." Computational and Structural Biotechnology Journal. 20(1).
Published in PLoS computational biology, 2021
Graph convolutional network to spead up de novo protein design
Recommended citation: Jack B Maguire, Daniele Grattarola, Vikram Khipple Mulligan, Eugene Klyshko, Hans Melo (2021). "XENet: Using a new graph convolution to accelerate the timeline for protein design on quantum computers." PLoS computational biology. 9 (17).