Macs in Chemistry

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A webinar demonstrating using Jupyter, the free iPython notebook

 

This is a recording of the March 2017 Global Health Compound Design meeting. A webinar demonstrating using Jupyter, the free iPython notebook.

https://youtu.be/XqyWctQxhNs

How to get started

Accessing Open Source Malaria data

Calculating physicochemical properties and plotting

Predicting AMES activity.



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Publishing computational notebooks with Binder

 

I've now written a couple of Jupyter notebooks and one of the issues that has come up is how to share the notebooks in a way that ensures the results will be reproducible in an environment when updates to components occur regularly.

Binder is a collection of tools for building and executing version-controlled computational environments that contain code, data, and interactive front ends, like Jupyter notebooks. It's 100% open source.

At a high level, Binder is designed to make the following workflow as easy as possible

  • Users specify a GitHub repository
  • Repository contents are used to build Docker images
  • Deploy containers on-demand in the browser on a cluster running Kubernetes

Common use cases include:

  • sharing scientific work
  • sharing journalism
  • running tutorials and demos with minimal setup
  • teaching courses

binder

If you want to find out more have a look at this blog post by the developers.


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Predicting AMES activity Jupyter Notebook

 

I've been experimenting with the use of Jupyter Notebooks (aka iPython Notebooks) as an electronic lab notebook but also a means to share computational models. The aim would be to see how easy it would be to share a model together with the associated training data together with an explanation of how the model was built and how it can be used for novel molecules.

The Ames test is a widely employed method that uses bacteria to test whether a given chemical can cause mutations in the DNA of the test organism. More formally, it is a biological assay to assess the mutagenic potential of chemical compounds. PNAS. 70 (8): 2281–5. doi

In this first notebook a random forest model to predict AMES activity is described….


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Molecular Design Toolkit

 

The Molecular Design Toolkit is an open source environment that aims to seamlessly integrated molecular simulation, visualization and cloud computing. It offers access to a large and still-growing set of computational modelling methods with a science-focused Python API, that can be easily installed using PIP. It is ideal for building into a Jupyter notebook. The API is designed to handle both small molecules and large bimolecular structures, molecular mechanics and QM calculations.

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There are a series of Youtube videos describing some of the functionality in more details, starting with this introduction.


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nteract a desktop-based, interactive computing application.

 

This blog post looks very interesting, a notebook environment for coding, data visualisation based on Juypter (aka iPython) notebooks

With nteract, you can create documents, that contain executable code, textual content, and images, and convey a computational narrative. Unlike Jupyter, your documents are stand-alone, cross-platform desktop applications, providing a seamless desktop experience and offline usage.

nteract can run your existing Jupyter notebooks without any modification, and supports multiple Jupyter kernels: Python, R, Julia, and JavaScript. Being a native Jupyter notebook, nteract applications can be easily saved to Domino, versioned, shared, and if needed, run on high-performance machines in the cloud, in your VPC, or on-premise.

More details are on GitHub.


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