Carlos Xavier Hernández is a PhD student in the Biophysics Program at Stanford University. He works with Vijay Pande, studying the molecular evolution of proteins and how it affects their structure, dynamics, and function.
Carlos graduated from Columbia University, where he majored in Applied Mathematics. There, he worked with Raul Rabadan and Stephen Goff studying RNA viruses. He has also spent time investigating chemokine receptors with J. Andrew McCammon at UCSD.
When it comes to proteins, sequence gives rise to function. However, it has become increasingly clear that proteins with wildly different sequences can yield quite homologous three-dimensional structures....
Molecules are small. Too small to be observed directly, in fact. In order to overcome this, Molecular Dynamics (MD) can be used to computationally model whole systems of molecules, like proteins, in atomistic detail....
Markov State Models
Markov state models (MSMs) are a powerful means of modeling the structure and dynamics of molecular systems, like proteins. An MSM is essentially a map of the conformational space a molecule explores....
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Title Author(s) Journal Citations Year 1 MDTraj: a modern, open library for the analysis of molecular dynamics trajectories RT McGibbon, KA Beauchamp, MP Harrigan, C Klein, JM Swails, ... Biophysical Journal 109 148 2015 2 Markov state models provide insights into dynamic modulation of protein function D Shukla, CX Hernández, JK Weber, VS Pande Accounts of chemical research 48 (2) 76 2015 3 MSMBuilder: statistical models for biomolecular dynamics MP Harrigan, MM Sultan, CX Hernández, BE Husic, P Eastman, ... Biophysical journal 112 (1) 40 2017 4 Osprey: Hyperparameter Optimization for Machine Learning RT McGibbon, CX Hernández, MP Harrigan, S Kearnes, MM Sultan, ... The Journal of Open Source Software 1 10 2016 5 MSMExplorer: Data Visualizations for Biomolecular Dynamics CX Hernández, MP Harrigan, MM Sultan, VS Pande The Journal of Open Source Software 2 (12) 6 2017 6 Structure‐based network analysis of an evolved g‐protein coupled receptor homodimer interface SE Nichols, CX Hernández, Y Wang, JA McCammon Protein Science 5 2013 7 Variational Encoding of Complex Dynamics CX Hernández, HK Wayment-Steele, MM Sultan, BE Husic, VS Pande arXiv preprint arXiv:1711.08576 3 2017 8 Understanding the origins of a pandemic virus CX Hernández, J Chan, H Khiabanian, R Rabadan arXiv preprint arXiv:1104.4568 2 2011 9 Using Deep Learning for Segmentation and Counting within Microscopy Data CX Hernández, MM Sultan, VS Pande arXiv preprint arXiv:1802.10548 2018 10 MDEntropy: Information-Theoretic Analyses for Molecular Dynamics CX Hernández, VS Pande The Journal of Open Source Software 2 2017 11 Kinetic Machine Learning Unravels Ligand-Directed Conformational Change of μ Opioid Receptor EN Feinberg, AB Farimani, CX Hernández, VS Pande bioRxiv 2017