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
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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
Building a simple SMILES based QSAR model with LSTM cells in PyTorch
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
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
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Cheminformania Consulting Unleash the Power of AI in Drug Discovery The surge in research and development driven by deep learning and modern neural network architectures has ignited
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This blog have a collection of posts centered around useful information and practical examples of how to do various cheminformatic tasks going more and more into deep
Using GraphINVENT to generate novel DRD2 actives
I have been writing a lot about how to use SMILES together with deep learning architectures such as RNNs and LSTM networks to perform various cheminformatic and
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