Code

This page contains links to the code that supports my publications as well as a set of links I find useful, they are more or less organized.

Repository supporting publications:

1. NiCOlit: https://github.com/truejulosdu13/NiCOlit

2. Target Specific Dataset Design: https://github.com/ReismanLab/regio_dataset_design

Links to Web Apps or GitHub pages I enjoyed:

Cheminformatics:

• RDKit-blog (Greg Landrum) : https://greglandrum.github.io/rdkit-blog/
• SMILES for beginners : https://www.cheminfo.org/
• RXNSMILES mapper App : http://cdb.ics.uci.edu/cgibin/reactionmap/ReactionMapWeb.py
• Coding in Chemistry (Nessa Carson) : https://supersciencegrl.co.uk/links/#Coding
• Peter Ertl website : https://peter-ertl.com/molecular/index.html
• Chemistry Toolkit (Martin Vérot) : http://perso.ens-lyon.fr/martin.verot/tools.php
• The Chemiscope : https://chemiscope.org/

Visualizing Chemical Space:

• Molplotly (Kjell Jorner) :tutorial.
• Chemplot
• The Chemiscope : https://chemiscope.org/

Books and Tutorials for Machine Learning in Chemistry:

• Deep Learning For Molecules and Materials (Andrew D. White) : https://dmol.pub/index.html
• Data Chemist Handbook : https://data-chemist-handbook.github.io/

More Computer Science Oriented:

• Understanding UMAP: https://pair-code.github.io/understanding-umap/
• Free online AI-courses (Piotr Skalski) : https://github.com/SkalskiP/courses

Open-source ressources and documentation:

• Molecular modeling applications: https://opensourcemolecularmodeling.github.io/#helper-applications
• Conferences summary by Nessa Carson: https://supersciencegrl.co.uk/conferences

Chemistry Data / Lesson Ressources:

• Visualization of molecular orbitals: OrbiMol
• Bond dissociation energies: UCSB website