Blog

May

A few weeks ago I completed the 16 week "Neural Networks for Machine Learning" on-line course from University of Montreal to deepen my understanding of Artificial Neural Networks and their fascinating properties. The course is taught by Professor, Geoffrey Hinton, which is one of the grand old men in ...

May

I was recently contacted by Gaurav Chaudhary, who is the CEO of Roots Analysis,  a firm that provide market research and consulting for the pharmaceutical industry. It turns out that Wildcard Pharmaceutical Consulting was mentioned in their report: Deep Learning in Drug Discovery and Diagnostics, 2017 ...

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

Medico Bazar 2017

Yesterday, Wildcard had a stand at the Medico Bazar 2017 at the Danish Technical University (DTU) in Lyngby. Medico Bazar brings together researchers, startups, investors and businesses in the medical device field. Although Wildcard is more focused on chemical and biological data, there seem to be a lot of interest in machine learning technologies, which led to a ...

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 ...

Feb

In another blog post I demonstrated how to build a deep neural network with Keras in Python to model some toxicity dataset from the Tox21 challenge. The network was however not systematically optimized, but merely put together with a few manually selected hyper parameters. Hyper parameters are understood as the parameters which are not tuned by the data ...

Feb

New option to follow comments

A new Wordpress plugin has been installed, which enables commenters to get notified when additional comments or replys are added to the blog posts. This did only work before for registered users of the Wordpress, such as writers and admins. This was rather unfortunate. But now it is not necessary to ...

Jan

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 network. I don't know how many layers a neural network actually has to have to be called "deep", but its a buzz word, so ...

Jan

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 space by using a deep learning neural autoencoder, by testing some of the newer tools based on neural networks which has shown promising results. ...