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Practical Cheminformatics Tutorials
A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.
PROPKA predicts the pKa values of ionizable groups in proteins and protein-ligand complexes based in the 3D structure.
Open Babel is a chemical toolbox designed to speak the many languages of chemical data.
scikit-learn: machine learning in Python
A Python package for calculating molecular features
🎨 Simplistic, responsive jekyll based open source theme
Machine learning predictions of bond dissociation energy
Computational chemistry benchmark data sets for non-covalent interactions
DBSTEP: DFT-based Steric Parameters - python-based tool to extract molecular shape and steric descriptors from essentially any structure format
Robust Molecular Structure Recognition with Image-to-Graph Generation
Compute Kinetic Isotope Effects using the Bigeleisen-Mayer equation
ANI-1 neural net potential with python interface (ASE)
A place to submit conda recipes before they become fully fledged conda-forge feedstocks
Python API for the extended tight binding program package
Semiempirical Extended Tight-Binding Program Package
Automated Monte Carlo Conformational Searching with Python
CREST - A program for the automated exploration of low-energy molecular chemical space.
Automated machine learning protocols that start from CSV databases of descriptors or SMILES and produce publication-quality results in Chemistry studies with only one command line.
Parsers and algorithms for computational chemistry logfiles
Python Code, shell scripts, templates, submission scripts and compchem specific workflows for use in the Paton Lab
Pyssian is an object oriented library for parsing Gaussian logfiles and input files which aims to facilitate the everyday scripting of computational chemists using Gaussian.