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2024	Streamlining NMR Chemical Shift Predictions for Intrinsically Disordered Proteins: Design of Ensembles with Dimensionality Reduction and Clustering Journal of Chemical Information and Modeling Michael J. Bakker, Amina Gaffour, Martin Juhás, Vojtěch Zapletal, Jakub Stošek, Lars A. Bratholm, Jana Pavlíková Přecechtělová
2023	Python in Chemistry: Physicochemical Tools Processes Fedor V. Ryzhkov, Yuliya E. Ryzhkova, Michail N. Elinson
2022	PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling BMC Bioinformatics Jayadev Joshi, Daniel Blankenberg
2022	Constrained iterative Hirshfeld charges: A variational approach The Journal of Chemical Physics Leila Pujal, Maximilian van Zyl, Esteban Vöhringer-Martinez, Toon Verstraelen, Patrick Bultinck, Paul W. Ayers, Farnaz Heidar-Zadeh
2021	Machine Learning of Analytical Electron Density in Large Molecules Through Message-Passing Journal of Chemical Information and Modeling Bruno Cuevas-Zuviría, Luis F. Pacios
2020	Cost-Effective Potential for Accurate Polarizable Embedding Calculations in Protein Environments Journal of Chemical Theory and Computation Peter Reinholdt, Erik Rosendahl Kjellgren, Casper Steinmann, Jógvan Magnus Haugaard Olsen
2015	ProCS15: a DFT-based chemical shift predictor for backbone and Cβatoms in proteins PeerJ Anders S. Larsen, Lars A. Bratholm, Anders S. Christensen, Maher Channir, Jan H. Jensen