AI3SD Video: Pitfalls and Gotcha’s with bioactivity data
AI3SD Video: Pitfalls and Gotcha’s with bioactivity data
John's talk focused on his experiences working with bioactivity data and drug discovery research along with some of the problems and errors that people have encountered when working in this sphere. In the past researchers could reasonably know ‘most' of the research within a field, but now we have much larger scale research, more participants and more data but without a lot of the groundwork being laid for good data sharing and reusability. Now there is a lot of messy data out there; inaccessible data, cryptic data and poorly described data. John talks about some of the bioactivity resources that are available for researchers and some of the successes that these data sources have had when handling large amounts of data. John gives plenty of tips about things to look out for when examining chemical and biological data, with plenty of examples.
AI3SD Event, Data Quality, Data Science, Data Sharing, Reproducible Research, Research, Research Data Management, Responsible Research, Training
Overington, John
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Kanza, Samantha
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Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Hooper, Victoria
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Knight, Nicola
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22 October 2020
Overington, John
b9ed00e6-ca24-477c-bb1c-4f113e85afb9
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84
Knight, Nicola
fbc21e18-095e-4c1a-a4bf-6277debf5c4b
Overington, John
(2020)
AI3SD Video: Pitfalls and Gotcha’s with bioactivity data.
Kanza, Samantha, Frey, Jeremy G., Hooper, Victoria and Knight, Nicola
(eds.)
AI3SD, PSDS & Patterns Failed it to Nailed it: Getting Data Sharing Right Seminar Series 2020, Online, Southampton, United Kingdom.
22 Oct - 03 Dec 2020.
(doi:10.5258/SOTON/P0068).
Record type:
Conference or Workshop Item
(Other)
Abstract
John's talk focused on his experiences working with bioactivity data and drug discovery research along with some of the problems and errors that people have encountered when working in this sphere. In the past researchers could reasonably know ‘most' of the research within a field, but now we have much larger scale research, more participants and more data but without a lot of the groundwork being laid for good data sharing and reusability. Now there is a lot of messy data out there; inaccessible data, cryptic data and poorly described data. John talks about some of the bioactivity resources that are available for researchers and some of the successes that these data sources have had when handling large amounts of data. John gives plenty of tips about things to look out for when examining chemical and biological data, with plenty of examples.
Video
FI2NI-Event1-Talk2-JohnOverington-221020
- Version of Record
More information
Published date: 22 October 2020
Additional Information:
John Overington holds a first degree in chemistry and studied for his PhD on comparative protein modelling, drug design, and sequence-structure relationships with Sir Tom Blundell at Birkbeck College, London. After a postdoctoral fellowship with the Imperial Cancer Research Fund, London, he joined Pfizer Central Research in the United Kingdom and eventually became manager of the Molecular Informatics, Structure and Design Department, where he was responsible for cheminformatics, structural biology, target analysis, and molecular modelling. He joined Inpharmatica in 2000; Inpharmatica was acquired by Galapagos NV in December 2006. There he was Senior Director, Discovery Informatics of the Galapagos subsidiary BioFocus DPI. In October 2008 he was appointed Team Leader, Chemogenomics at the European Molecular Biology Laboratory (EMBL), working at the European Bioinformatics Institute (EMBL-EBI) in Hinxton, U.K. where he established and ran the ChEMBL group. Following that, he spent two years as VP Biomedical Informatics at BenevolentAI. He became Chief Informatics Officer at Medicines Discovery Catapult (MDC) in 2017.
Venue - Dates:
AI3SD, PSDS & Patterns Failed it to Nailed it: Getting Data Sharing Right Seminar Series 2020, Online, Southampton, United Kingdom, 2020-10-22 - 2020-12-03
Keywords:
AI3SD Event, Data Quality, Data Science, Data Sharing, Reproducible Research, Research, Research Data Management, Responsible Research, Training
Identifiers
Local EPrints ID: 447530
URI: http://eprints.soton.ac.uk/id/eprint/447530
PURE UUID: 07f1bd3f-dec1-49d0-883e-ae6a971426ba
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Date deposited: 15 Mar 2021 17:38
Last modified: 17 Mar 2024 03:57
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Author:
John Overington
Editor:
Victoria Hooper
Editor:
Nicola Knight
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