Open Data for Chemistry

10 November 2020 16:00 - 12 November 2020 15:30, United Kingdom


Introduction
Huge quantities of data are generated in the chemical sciences although frequently these data are behind paywalls or protected intellectual property of organisations. Recently however there has been a tendency for more openness in scientific data in general and specifically the chemical sciences. There is now a large quantity of open data mined from the literature over decades offering new opportunities to learn from these data thereby improving scientific endeavour. However ensuring data accessibility, discovery and quality is still a major issue. The meeting will offer guidance on data curation and wrangling in order to be able to be applied effectively.

Presentations will be delivered over three two-hour sessions.

10 November  16.00  - 18.00
Prof John Overington:  Large-scale bioactivity data for drug discovery - some history and the future
Dr Samantha Kanza:  Semantic Web 4 Chemistry - How to use these technologies effectively - and what not to do!
Dr Emma Schymanski:  Digital Detective Work: Connecting cheminformatics, mass spectrometry and our environment via open data

11 November  11.00 - 13.00
Dr Kim Jelfs:  Exploring chemical space for molecular material discovery
Suzanna Ward:  title to be confirmed
Dr Ed Griffen:  Learning from Massive Scale ADMET and potency data analysis

12 November  13.30 - 15.30
Dr Barbara Zdrazil:  Mining data from the open domain for modelling transporter-mediated toxicity
Prof Matthew Todd:  A Frosted Window: Sharing chemical data in open drug discovery networks
Dr Nicole Jung:  Chemotion: Infrastructure to provide open data

Registration
This event will be free to attend but registration is required.

This meeting is part of a five-day series exploring the theme of open chemical science. Further information about the series can be found at the link on this page.
 
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