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"Using Markov state models to accelerate free-energy simulations“ - @mmsltn talks about recent progress in Molecular Dynamics + Machine Learning.
Interesting preprint from Frank Noé: "Machine Learning for Molecular Dynamics on Long Timescales" arxiv.org/abs/1812.07669 #CompChem #MachineLearning
Latest article published in our New Tools and Methods section in JPCA is on #MachineLearning: Machine-Learning Based Stacked Ensemble Model for Accurate Analysis of Molecular Dynamics Simulations. #MD #Compchem pubs.acs.org/doi/10.1021/ac…
✨📊 If you will be around #NeurIPS2019 this Saturday, make sure to check out these two workshops on JAX: 1) JAX-MD: End-to-end Molecular Dynamics in Python @ 9:30am ⚛️ nips.cc/Conferences/20… 2) JAX: accelerated machine learning research @ 2:50pm ⚡ neurips.cc/Conferences/20…
Multi-Target Dopamine D3 Receptor Modulators: Actionable Knowledge for Drug Design from Molecular Dynamics and Machine Learning by Giovanni Bottegoni & co-workers bit.ly/2KpoOR4
Molecular dynamics, machine learning create hyper-predictive drug discovery models news.ncsu.edu/?p=447601
New paper: Machine Learning of Coarse-Grained Molecular Dynamics Force Fields: I've computed (tentative) credits for the new methods paper pubs.acs.org/doi/10.1021/ac… ("Wang et al."). Congratulations to all co-authors, and especially Adrià and Gianni who did… dlvr.it/RK86mS
Michele Parrinello, a renowned italian investigator, will be giving the opening conference of #StatPhys27 about machine learning and molecular dynamics.
Researchers from @CompBasel use density maps for hydration site occupancy to train a convolutional neural network in order to predict protein-ligand binding more accurately compared to common scoring functions nature.com/articles/s4200…
Top #tweeted story in #structbio: GitHub - sha256feng/mldl-md-dynamics: A repository of update in molecular dynamics field by recent progress in machine learning and deep learning. github.com/sha256feng/mld…, see more tweetedtimes.com/v/1344?s=tnp
DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics arxiv.org/abs/1712.03641 #compchem #preprint
Nice work that combines MD and an autoencoder to improve sampling... Coupling Molecular Dynamics and Deep Learning to Mine Protein Conformational Space cell.com/structure/full…
cell.com
Coupling Molecular Dynamics and Deep Learning to Mine Protein Conformational Space
Degiacomi presents a usage of generative neural networks for the characterization of the conformational space of proteins featuring domain-level dynamics. The network can generate protein-like...
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