I found some interesting toxicology datasets from the Tox21 challenge, and wanted to see if it was possible to build a toxicology predictor using a deep neural

I found some interesting toxicology datasets from the Tox21 challenge, and wanted to see if it was possible to build a toxicology predictor using a deep neural
In the last blogpost the battle tested principal components analysis (PCA) was used as a dimensionality reduction tool. This time we’ll take a deeper look into chemical
As covered before, chemical space is huge. So it could be nice if this multidimensional molecular space could be reduced and visualized to get an idea about
Neural networks are interesting models underlying much of the newest AI applications and algorithms. Recent advances in training algorithms and GPU enabled code together with publicly available
Neural Networks are interesting algorithms, but sometimes also a bit spooky. In this blog post I explore the possibilities for teaching the neural networks to generate completely
I’m looking forward for the first to attend the RDKit user group meeting from 26-28 October 2016 in Basel, Switzerland. RDKit is an open source chemoinformatics toolkit
Inspired by the success reported in my last blog post [Link] about the open source docking program rDock [http://rdock.sourceforge.net], I decided to investigate the docking accuracy performance
Last time i tested the basics of the docking program rDock; Installation, basic setup and docking, as well as had a brief walkthrough about how to post-process
rDock is an open source docking program, trying to solve the same kind of scientific questions as Autodock Vina, which I have covered in a couple of
In the two previous blog posts Ligand docking with Smina and Never use re-docking for …, it was demonstrated how easy it is to dock a small ligand