SMILES enumeration and vectorization for Keras

The SMILES enumeration code at GitHub has been revamped and revised into an object for easier use. It can work in conjunction with a SMILES iterator object that give on-the-fly enumeration and vectorization for training of SMILES based Recurrent Neural Network (RNN) models of molecules for ...
Better Deep Learning Neural Networks with SMILES Enumeration of Molecular Data

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 ...
Learn how to improve SMILES based molecular autoencoders with heteroencoders

Earlier I wrote a blog post about how to build SMILES based autoencoders in Keras. It has since been a much visited page, so the topic seems interesting for a lot of people, thank you for reading. One thing that I worried about was how nearby molecules seem more related when comparing the SMILES strings rather than the molecules. ...
Chemical Deep Learning
Deep learning is a specialized part of machine learning. It have come to have a sort of magical cling to the buzz word, but there is no magic, only mathematical modelling and data science. It distinguishes itself from other machine learning models by having a data driven feature extraction, ...
About Us
I founded the company in 2010 to provide flexible IT services and advanced data analytics for former colleges and other people in my network on a part-time basis beside my post doc projects. After a while I started to realize how much value I can provide by understanding and bridging scientific research ...
Learn how to teach your computer to “See” Chemistry: Free Chemception models with RDKit and Keras

The film Inception with Leonardo Di Caprio is about dreams in dreams, and gave rise to the meme "We need to go deeper". The title has also given name to the Inception networks used by Google in their Inception network. I recently stumbled across two interesting ...