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

Cheminformatics in Excel part 2: RDKit4Excel

Esben Jannik Bjerrum/ November 21, 2017

Previously I wrote about how to use the xlwings project to get RDKit functionality directly in Excel. Well, it wasn’t that directly as there were some intermediate

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Cheminformatics in Excel: linking RDKit with Xlwings

Esben Jannik Bjerrum/ August 11, 2017

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

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Can children fold proteins?

Esben Jannik Bjerrum/ July 31, 2017

Can children fold proteins? During the summer holidays I volunteered to hold a workshop about protein folding at the summer camp for Gifted Children Denmark. The idea

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Programming a simple molecular GUI browser with model-view architecture (MVC) using Python with PySide or PyQt and RDKit

Esben Jannik Bjerrum/ June 2, 2017

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

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Better Deep Learning Neural Networks with SMILES Enumeration of Molecular Data

Esben Jannik Bjerrum/ March 23, 2017

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

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Tune your deep tox neural network with free tools

Esben Jannik Bjerrum/ February 7, 2017

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

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A deep Tox21 neural network with RDKit and Keras

Esben Jannik Bjerrum/ January 15, 2017

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

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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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Peeking into the chemical space using free tools

Esben Jannik Bjerrum/ December 19, 2016

As covered before, chemical space is huge. So it could be nice if this multidimensional molecular space could be reduced and visualized to get an idea about

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Molecular neural network models with RDKit and Keras in Python

Esben Jannik Bjerrum/ December 6, 2016

Neural networks are interesting models underlying much of the newest AI applications and algorithms. Recent advances in training algorithms and GPU enabled code together with publicly available

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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…

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