Moved to @ltchong.bsky.social. Professor, @PittChem. Computational biophysicist, @westpasoftware for rare event sampling, @ambermdprog force field developer.
Pittsburgh, PA
Joined April 2009
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Lillian Chong retweeted
pixi 0.30.0 is now available! In this release I contributed `pixi project export conda-explicit-spec` that allows you to export a pixi.lock file to a conda explicit spec that can be used with conda/mamba. Full release notes are here github.com/prefix-dev/pixi/r… @prefix_dev
Lillian Chong retweeted
Check out some recent work integrating MD simulations with rare event sampling and DeepDriveMD with the wonderful @ltchong and our group. Really enjoyed the research, discussions, and the directions this work is taking!
Unsupervised learning of progress coordinates during weighted ensemble simulations: Application to millisecond protein folding
- Improve rare events in protein folding (e.g., state transitions) through weighted ensemble simulation and an unsupervised deep learning model.
- Use a convolutional VAE to compress contact maps into latent space, and applies a Local Outlier Factor to identify outlier conformations, which are then replicated in the simulation.
- Training the CVAE on-the-fly works better than using a pretrained model.
Preprint: biorxiv.org/content/10.1101/…
Lillian Chong retweeted
My department seeks to hire a new tenure-track assistant professor in computational biophysics, broadly defined, to complement and grow Notre Dame's existing biophysics community. Please share -- and consider applying!
apply.interfolio.com/152715
Lillian Chong retweeted
#BreakingNews Thanks to @lexinc_'s incredible work, #MDANCE (github.com/mqcomplab/MDANCE) is available as a kit in @mdanalysis! (github.com/MDAnalysis/MDAKit…). Thanks @orbeckst for the guidance.
#compchem #MachineLearning
Lillian Chong retweeted
Having trouble visualizing your data from WESTPA?
Try WEDAP! A user-friendly plotting package from @darianyang and @ltchong (1/4)
pubs.acs.org/doi/10.1021/acs…
A fast, discriminating clustering algorithm from @GroupQuintana!
#compchem Good read!: k-Means NANI: An Improved Clustering Algorithm for Molecular Dynamics Simulations doi.org/10.1021/acs.jctc.4c0…
Lillian Chong retweeted
In episode 13 of the Phase Space Invaders #podcast 🎙️, my guest is Daniel Zuckerman @DMZuckermanLab! Listen to the episode on Spotify or other podcast platforms: open.spotify.com/episode/1kM…
Prompted by Daniel's passion for sharing knowledge, we discuss the question of writing #textbooks for the scientific audience 📖, including the key ingredients for clarity and depth of insight. Then, we explore the advantages and pitfalls of a trajectory-centric view of molecular #biophysics in its quest to integrate kinetics, thermodynamics, and #nonequilibrium processes into an intuitive framework.
For the curious ones, Daniel's blog can be found here: statisticalbiophysicsblog.or…
As always, happy to hear your feedback!
Lillian Chong retweeted
Thrilled to share that my thesis manuscript is out!
Here, we used WESTPA2 to show that mutations in Abl1 lead to drug resistance by dramatically shifting relative state populations, impacting the conformational search step of binding.
Link below:
biorxiv.org/content/10.1101/…
Lillian Chong retweeted
New Practical Cheminformatics Post, "Generative Molecular Design Isn't As Easy As People Make It Look", practicalcheminformatics.blo…
Lillian Chong retweeted
Bayesian inference is vital to interpreting experimental data. Learn the relationship of BI to statistical mechanics including important nuances, and get a ‘sampling’ of modern Monte Carlo methods for BI.
pubs.acs.org/doi/10.1021/acs…
Revisiting Textbook Azide-Clock Reactions: A “Propeller-Crawling” Mechanism Explains Differences in Rates | Journal of the American Chemical Society @ltchong @PittChem @PittTweet #Azide #Clock #PropellerCrawling #Mechanism #Rates pubs.acs.org/doi/10.1021/jac…
