Tien Phan's repositories
football-project
Calculate surface tension of a "football" shape of actin using MC simulation
AF_Cluster
Predict multiple protein conformations using sequence clustering and AlphaFold2.
al-folio
A beautiful, simple, clean, and responsive Jekyll theme for academics
alphaflow
AlphaFold Meets Flow Matching for Generating Protein Ensembles
Awesome-Diffusion-Models
A collection of resources and papers on Diffusion Models
HP1paralogs-simulations
Scripts to run the simulations of HP1 paralogs
CmuMD
CmuMD implementation for PLUMED2
CSpred
UCBShift is a program for predicting chemical shifts for backbone atoms and β-carbon of a protein in solution. It utilizes a machine learning module that makes predictions from features extracted from the 3D structures of the proteins.
deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
deepmd-kit
A deep learning package for many-body potential energy representation and molecular dynamics
ELViM
ELViM is a method for visualizing the energy landscapes of biomolecules simulations.
FRETpredict
Software for the prediction of FRET data from conformational ensembles.
idpGPT
GPT models of PLMs trained to generate novel protein sequences when supplied with a prompt
idpsam
Generate intrinsically disordered peptide conformations via machine learning
making-it-rain
Cloud-based molecular simulations for everyone
micrograd
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
msmbuilder2022
Statistical models for biomolecular dynamics
msmhelper
Helper function for Markov State Models
NeuralPLexer
NeuralPLexer: State-specific protein-ligand complex structure prediction with a multi-scale deep generative model
paper-qa
LLM Chain for answering questions from documents with citations
progen
Official release of the ProGen models
pyDR
New implementation of pyDIFRATE
pyDR_tutorial
Tutorial files for pyDR
seekr2
Simulation-Enabled Estimation of Kinetic Rates - Version 2
system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.