Hi there๐
publications ๐
You can also check out my google scholar for an up-to-date list.
D. Nagel and T. Bereau, Fokker-Planck Score Learning: Efficient Free-Energy Estimation Under Periodic Boundary Conditions, arXiv, 2025
D. Nagel, G. Diez, and G. Stock, Accurate estimation of the normalized mutual information of multidimensional data, J. Chem. Phys., 161, 054108, 2024
D. Nagel, S. Sartore, and G. Stock, Towards a Benchmark for Markov State Models: The Folding of HP35, J. Phys. Chem. Lett, 14, 31, 2023
D. Nagel and G. Stock, msmhelper: A Python package for Markov state modeling of protein dynamics, J. Open Source Soft., 8, 5339, 2023
D. Nagel, S. Sartore, and G. Stock, Selecting Features for Markov Modeling: A Case Study on HP35, J. Chem. Theory Comput., 19, 3391, 2023
G. Diez, D. Nagel, and G. Stock, Correlation-Based Feature Selection to Identify Functional Dynamics in Proteins, J. Chem. Theory Comput., 18, 5079, 2022
D. Nagel, A. Weber, and G. Stock, MSMPathfinder: Identification of Pathways in Markov State Models, J. Chem. Theory Comput., 16, 7874, 2020
D. Nagel, A. Weber, B. Lickert, and G. Stock, Dynamical coring of Markov state models, J. Chem. Phys., 150, 094111, 2019
software ๐ฟ
The following list is not complete. Please refer to my Github/Gitlab pages for more details.
efficient free-energy estimation under periodic boundary conditions
#python #jax #diffusion-model #ml
a wrapper for creating easily beautiful matplotlib figures
#python #matplotlib
a time sequence analysis tool for employing Markov state models
#python #markovchain #numba #dataanalysis
a generalized Kraskov estimator for estimating normalized MI
#python #dataanalysis #ml
2023 © Daniel Nagel