Machine Learning Coarse-Grained Potentials of Protein Thermodynamics

14 December 2022

Papers citing "Machine Learning Coarse-Grained Potentials of Protein Thermodynamics"

6 / 6 papers shown

Title
Deep Neural Network for Phonon-Assisted Optical Spectra in Semiconductors Qiangqiang Gu S. K. Pandey Zhanghao Zhouyin 59 0 0 02 Feb 2025
Deep Signature: Characterization of Large-Scale Molecular Dynamics Tiexin Qin Mengxu Zhu Chunyang Li Terry Lyons Hong Yan Haoliang Li 28 0 0 03 Oct 2024
DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein Traces Michael S. Jones Kirill Shmilovich Andrew L. Ferguson DiffM 34 12 0 23 Jul 2023
Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations Oliver T. Unke M. Stohr Stefan Ganscha Thomas Unterthiner Hartmut Maennel ... Daniel Ahlin M. Gastegger L. M. Sandonas A. Tkatchenko Klaus-Robert Muller AI4CE 35 18 0 17 May 2022
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 158 245 0 01 May 2021
Coarse Graining Molecular Dynamics with Graph Neural Networks B. Husic N. Charron Dominik Lemm Jiang Wang Adria Pérez ... Yaoyi Chen Simon Olsson Gianni de Fabritiis Frank Noé C. Clementi AI4CE 33 158 0 22 Jul 2020