Science

Mar

The process of expanding an otherwise limited dataset in order to more efficiently train a neural network is known as Data Augmentation For images there have been used a variety of techniques, such as flipping, rotation, sub-segmenting and cropping, zooming. The mirror image of a cat is ...

Mar

Deep Neural Networks and Spectroscopic Data - a chemometric study A Masters project is available in a collaboration between Wildcard Pharmaceutical Consulting and Department of Food, Spectroscopy and Chemometrics, KU. We are looking for a motivated student with interest in spectroscopy and computer programming to take on a project involving ...

Mar

Congratulations to Nadia Lund

Yesterday I had the pleasure to be external examiner at Nadia Lunds Master thesis defense. She delivered a brilliant and clear presentation of her project entitled "GPCR Structural Switches Stabilizing Specific States and Signals", where she had developed and used a sequence signature method to identify potential amino acid residues which are most likely involved in the GPCR G-Protein ...

Nov

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 novel drug like molecules. I have experimented for some time with recurrent neural networks with the LSTM architecture. In short, recurrent neural networks differ from more traditional feed forward neural networks because they do ...

May

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 using Smina, and how deceptively accurate a docking program can be when using re-docking rather that cross-docking. It is however possible to re-tune the docking function to a specific purpose using machine ...