This is your periodic reminder that MDPI is a predatory publisher and must be avoided. #compchem #AcademicTwitter
Going through proposals, I noticed that several PIs publish in MDPI journals, as some offer a (somehow…) decent IF. Just please go to more serious and respected journals; MDPI won’t do any good to your reputation, nor to your CV. My two cents …
We are looking for a postdoc in #computchem #machinelearning at @UOW @arc_qubic @MolHorizons #chemjobs #ozchem · 3 years, full-time · Level A: $90,795 - $106,374 + 17% Superannuation · Deadline: 01/09/2024 Apply bit.ly/UOW_QUBIC_Post… to join us in the beautiful Wollongong!
Cool!
An interesting coarse-grained methodology by Sugita and co-workers to simulate phase separation.. nature.com/articles/s4146…
Check our lastest work on LLPS @PCCP 😀 Understanding and fine tuning the propensity of ATP-driven liquid–liquid phase separation with oligolysine - now published in Physical Chemistry Chemical Physics pubs.rsc.org/en/content/art…
Currently on @ChemRxiv, just accepted for publication in @JChemPhys! 🎉 👉 doi.org/10.26434/chemr… In this paper, we test several neural network potentials for #water based on the DeePMD framework, which were derived by both us and other researchers, using our MB-pol…
We're excited to announce SPICE 2.0, a new foundation QM dataset for building ML potentials for biomolecular simulation! 🚀 💊 13K new PubChem molecules 🌊 water clusters and solvated molecules 🤝 amino acid-ligand pairs ⚛️ more elements (B, Si) github.com/openmm/spice-d…
Join us and explore Ion-channel trends with global experts on March 22nd, 8-10 AM PST via Zoom. Connect, learn, and grow!!! @TharakaTD @JeromeMechBio @lyna_yunluo @BiophysicalSoc @wojciechkopec3 @htkratochvil @LiangFeng_chem
DP/MM: A Hybrid Model for Zinc–Protein Interactions in Molecular Dynamics | The Journal of Physical Chemistry Letters pubs.acs.org/doi/10.1021/ac… Finally see the deep potential hybrid with classical force fields over biological systems!!!
LAMMPS tutorials inputs and files are now more recognizable thanks to ascii-image-converter (github.com/TheZoraiz/asci…). Completely useless, but I love it.
First corresponding author paper _at_ UC Irvine. Nice collaboration with @WuYongxian21 and @rayluo
Can neural networks (NN) learn to construct molecule surfaces? Researchers from @UCIrvine propose a universal NN framework to build molecule surfaces from point cloud data, achieving more than 26 times speedup by harnessing GPU's computing power. go.acs.org/6Za
Honored to participate in it😀
Out now! Mingyue Zheng and colleagues propose a physics-informed deep learning model to predict the relative binding affinity of ligands. nature.com/articles/s4358…
#compchem Good read: Understanding the Anomalous Diffusion of Water in Aqueous Electrolytes Using Machine Learned Potentials doi.org/10.1021/acs.jp…
Watch the amazing journey of Trp-Cage as it folds into its native state!👀 Our neural network-based coarse-grained simulation reveals the magic of protein dynamics ▶️ youtu.be/l9MI6XQZjnU. Read more about it here: nature.com/articles/s4146… 📚
Two new open positions in Machine Learning have just been posted on the MolSSI website: One with D.E. Shaw Research in NYC and the other for a postdoctoral position at Linkoping University in Sweden (Nov 3 application deadline for the latter). #compchem molssi.org/job-opportunit…
If you are interested in the ins and outs of the state-of-the-art of chemical specific ("pragmatic") coarse-grain molecular dynamics simulations, this detailed review is worth your time! Thanks @SouzaPauloCT for involving us!
Happy to share our review about pragmatic #CGprotein models, a fascinating intersection of physics-based and a top-down approaches used to study biological processes involving large protein assemblies or long time scale dynamics. Published in @JCIM_JCTC pubs.acs.org/doi/10.1021/ac…
Now accepting applications for a postdoctoral position in my group at Freie Universität Berlin. Come join us! fu-berlin.de/universitaet/b…
We are excited to announce the release of MOPAC 22.1.0! The main new feature is the PM6-ORG semiempirical model optimized for proteins and other biomolecules, alongside other minor updates. Available now on GitHub at github.com/openmopac/mopac and conda-forge. #compchem
United States Trends
- 1. Jokic 11,7 B posts
- 2. Pete 291 B posts
- 3. DeSantis 34 B posts
- 4. Kerr 6.998 posts
- 5. Mavs 12,1 B posts
- 6. Podz 3.183 posts
- 7. Clemson 24,9 B posts
- 8. Nuggets 16,4 B posts
- 9. Brea 2.587 posts
- 10. Kentucky 19,1 B posts
- 11. Wiggins 2.724 posts
- 12. Jamal Murray 1.466 posts
- 13. Bama 41 B posts
- 14. Marcus Smart 2.573 posts
- 15. Kuminga 2.278 posts
- 16. NBA Cup 14,7 B posts
- 17. Grizzlies 6.214 posts
- 18. #MFFL 4.008 posts
- 19. azealia 3.646 posts
- 20. #GSWvsDEN N/A
Something went wrong.
Something went wrong.