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Cheminformania

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    • Esben Jannik Bjerrum
  • Blog
  • About
    • About Cheminformania
    • Esben Jannik Bjerrum

Using GraphINVENT to generate novel DRD2 actives

Esbenbjerrum/ November 2, 2020

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

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Building a simple QSAR model using a feed forward neural network in PyTorch

Esbenbjerrum/ May 1, 2020

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 Keras as a stand-alone is now no longer active developed, but are instead now

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A deeper look into chemical space with neural autoencoders

Esben Jannik Bjerrum/ January 3, 2017

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

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Recent Comments

  1. esbenbjerrum on A deep Tox21 neural network with RDKit and KerasJanuary 22, 2025

    Yes, it's a single-task network. For a multi-task network, you would need to increase the number of output-neurons to fit…

  2. Elon on A deep Tox21 neural network with RDKit and KerasJanuary 20, 2025

    If I understand correctly, it seems you have used a single-label approach 'SR-MMP' instead of a multi layer approach using…

  3. esbenbjerrum on Generating Unusual Molecules with Genetic AlgorithmsNovember 24, 2024

    Yes, of course that is possible;-) I wrote a follow-up blogpost using molecular log-likelihood estimation to accomplish just that Generating…

Popular Pages

  • Never do this mistake when using Feature Selection
  • rdEditor: An open-source molecular editor based using Python, PySide2 and RDKit
  • A deeper look into chemical space with neural autoencoders
  • The Good, the Bad and the Ugly RDKit molecules
  • Non-conditional De Novo molecular Generation with Transformer Encoders

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