Yesterday, Cancer Research UK press released the launch of the first full version of canSAR - the Institute of Cancer Research's integrated cancer research and drug discovery resource. canSAR integrates large volumes of disparate data covering most aspects of cancer biology and chemistry, and is an example of how to complement the chEMBL database with therapeutic area specific knowledge. canSAR integrates biological annotation, gene expression, RNA interference studies, structural biology and protein interaction network data - as well as chemical and pharmacological data. It contains annotation on the entire human proteome, and contains >8 million experimental data points including RNAi and chemical screening data. For full release notes please see canSAR news. canSAR is updated monthly. As well as the wonderful chEMBL, the data in canSAR comes from a large number of sources, including ArrayExpress, PDBe, ROCK, STRING, Genomics of Drug Sensitivity in Cancer, COSMIC, BindingDB, SCOP, PFAM- we (at the ICR) are grateful to our friends at all these places for their help. In the new year, we will be holding a series of webinars and walkthroughs, and details of these will be posted on the ChEMBL-og.
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