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A Django-powered website for Reaction Mechanism Generator (RMG)
A deep learning method that identifies improved protein conformational states in trajectory data from refinement simulations
Retrosynthesis reaction prediction using Transformer sequence to sequence models and SMILES based data augmentation
Implementation of Retrosynthesis Prediction with Conditional Graph Logic Network
A curated list of Python packages related to chemistry
Documenting the explosion of packages in the standard ecosystem!
Code accompanying a 180 minute tutorial on June 3rd, 2020 about Python package structure, installation with pip, unit testing, automation, CLI building, and more.
Data and model repository for the ASKCOS application
Software package for computer aided synthesis planning
Ancillary methods for the autoprotocol-python library
A web application to display the retrosynthetic reaction pathway using FLASK
This project introduces a novel single-step retrosynthesis approach based on chemical compound substructures and fingerprint descriptors.
Python package for building fitness landscapes from protein lattice models
python program for analyzing isothermal titration calorimetry data
Protein-Ligand Benchmark Dataset for Free Energy Calculations
Kinetically Discriminatory Metric Learning -- a plugin for MSMBuilder
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Data repository for: Application of the Ab Initio Nanoreactor to the Development of a New Peroxide-Driven Ketone Oxidation Reaction
Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimization of Machine Learning Algorithms. Jasper Snoek, Hugo Laroche…
Deep Reinforcement Learning for de-novo Drug Design
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Implementation of the SolTranNet tool utilizing the molecular transformer to predict aqueous solubility
Comprehensive library for fast, GPU accelerated molecular gridding for deep learning workflows