Last blog-post I showed how to use PyTorch to build a feed forward neural network model for molecular property prediction (QSAR: Quantitative structure-activity relationship). RDKit was used
Building a simple QSAR model using a feed forward neural network in PyTorch
In my previous blogposts I’ve entirely been using Keras for my neural networks. Keras as a stand-alone is now no longer active developed, but are instead now
Master your molecule generator 2. Direct steering of conditional recurrent neural networks (cRNNs)
Long time ago in a GPU far-far away, the deep learning rebels are happy. They have created new ways of working with chemistry using deep learning technology
Learn how to make a jupyter notebook widget for annotation of atom properties
Not so long ago Greg Landrum published a blog post with an example of how the SVG rendering from RDKit in a jupyter notebook can be
rdEditor: An open-source molecular editor based using Python, PySide2 and RDKit
At the RDKit UGM 2018 in Cambridge I made a lightning talk where I show cased rdEditor. I’ve wanted to write a bit about it for some
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
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
Cheminformatics in Excel: linking RDKit with Xlwings
Excel is widely used in businesses all over the world and can be used for many diverse tasks due to the flexibility of the program. I’ve been
Programming a simple molecular GUI browser with model-view architecture (MVC) using Python with PySide or PyQt and RDKit
One of the more popular blog post based on monthly visitors is the old Create a Simple Object Oriented GUIDE GUI in MatLAB, but since I don’t
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