Target Prediction IPython Notebook Tutorial

As promised in the previous post, the ChEMBL target prediction models are now available to download from here. Furthermore, here is an IPython Notebook that showcases how the models can be used in Python. As usual, your feedback is very welcome.

George

Comments

Chris said…

Many thanks

Chris

11 April 2014 at 15:44

Iain said…

Really useful, thanks

12 May 2014 at 14:50

Chris said…

These models require scikit-learn==0.14.1

I now have them running in a virtual environment, any plans to update them?

30 June 2015 at 17:10

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A python client for accessing ChEMBL web services

Motivation The CheMBL Web Services provide simple reliable programmatic access to the data stored in ChEMBL database. RESTful API approaches are quite easy to master in most languages but still require writing a few lines of code. Additionally, it can be a challenging task to write a nontrivial application using REST without any examples. These factors were the motivation for us to write a small client library for accessing web services from Python. Why Python? We choose this language because Python has become extremely popular (and still growing in use) in scientific applications; there are several Open Source chemical toolkits available in this language, and so the wealth of ChEMBL resources and functionality of those toolkits can be easily combined. Moreover, Python is a very web-friendly language and we wanted to show how easy complex resource acquisition can be expressed in Python. Reinventing the wheel? There are already some libraries providing access to ChEMBL d

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