nsf-c-cas Goto Github PK

acidamine_descriptor_predict

Code for descriptor collection and modeling enclosed within the paper: Rapid Prediction of Conformationally-Dependent DFT-Level Descriptors using Graph Neural Networks for Carboxylic Acids and Alkyl Amines.

alfabet

Machine learning predictions of bond dissociation energy

auto-qchem

Quantum mechanical descriptor generation

bde-db

A collection of 290,664 Homolytic Bond Dissociation Enthalpies for Small Organic Molecules

cascade

CAlculation of NMR using Deep LEarning

dbstep

DBSTEP: DFT-based Steric Parameters - python-based tool to extract molecular shape and steric descriptors from essentially any structure format

edbo

Experimental Design via Bayesian Optimization

goodvibes

Calculate quasi-harmonic free energies from Gaussian output files with temperature and other corrections

q2mm

Quantum to Molecular Mechanics (Q2MM)

q2mm-2

rxnpredict

Predicting reaction performance using machine learning

rxnpredict-2

Doyle Lab: predicting reaction performance using machine learning

threshold

Python tool to assess data for single-parameter thresholds

wsterimol

Generate Boltzmann-weighted Sterimol Steric Parameters for Conformationally-Flexible Substituents

yield-rxn

Code for the paper: Graph Neural Networks for Predicting Chemical Reaction Performance