The University of Southampton
University of Southampton Institutional Repository

AI3SD Video: Machine Learning for Early Stage Drug Discovery

AI3SD Video: Machine Learning for Early Stage Drug Discovery
AI3SD Video: Machine Learning for Early Stage Drug Discovery
Professor Charlotte Deane from the University of Oxford speaks about some of the work her research group have done on Machine Learning for Early Stage Drug Discovery to give a flavour of the different kinds of approaches they have been looking at. These run from predicting whether molecules will bind or not bind to a given protein target, to trying to remove biases from that kind of work, to finally how do we generate novel molecules in the protein binding sites.
AI, AI3SD Event, Artificial intelligence, Chemistry, Drug Discovery, Machine Intelligence, Machine learning, ML, Molecules Discovery
Deane, Charlotte
4884ff02-b511-41ab-9f97-c7729c75f4f1
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84
Deane, Charlotte
4884ff02-b511-41ab-9f97-c7729c75f4f1
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84

Deane, Charlotte (2020) AI3SD Video: Machine Learning for Early Stage Drug Discovery. Kanza, Samantha, Frey, Jeremy G., Niranjan, Mahesan and Hooper, Victoria (eds.) AI3SD Summer Seminar Series 2020, Online, Southampton, United Kingdom. 01 Jul - 23 Sep 2020. (doi:10.5258/SOTON/P0056).

Record type: Conference or Workshop Item (Other)

Abstract

Professor Charlotte Deane from the University of Oxford speaks about some of the work her research group have done on Machine Learning for Early Stage Drug Discovery to give a flavour of the different kinds of approaches they have been looking at. These run from predicting whether molecules will bind or not bind to a given protein target, to trying to remove biases from that kind of work, to finally how do we generate novel molecules in the protein binding sites.

Video
AI3SDOnlineSeminarSeries-10-CD-040920 - Version of Record
Available under License Creative Commons Attribution.
Download (459MB)

More information

Published date: 4 September 2020
Additional Information: Charlotte is Professor of Structural Bioinformatics at the Department of Statistics, University of Oxford and Deputy Executive Chair of the Engineering and Physical Sciences Research Council (EPSRC). At Oxford, Charlotte leads the Oxford Protein Informatics Group, who work on diverse problems across protein structure, interaction networks and small molecule drug discovery; combining theoretical and empirical analysis with special interest in AI. She collaborates with experimentalists in academia and industry in experiment design to leverage the power of computation for biological insight. Her work focusses on the development of novel algorithms, tools and databases that are openly available to the community. Examples include SAbDab, SAbPred, PanDDA and MEMOIR. These tools are widely used web resources and are also part of several Pharma drug discovery pipelines. Charlotte has consulted extensively with industry and has set up a consulting arm within her own research group as a way of promoting industrial interaction and use of the group’s software tools.
Venue - Dates: AI3SD Summer Seminar Series 2020, Online, Southampton, United Kingdom, 2020-07-01 - 2020-09-23
Keywords: AI, AI3SD Event, Artificial intelligence, Chemistry, Drug Discovery, Machine Intelligence, Machine learning, ML, Molecules Discovery

Identifiers

Local EPrints ID: 447162
URI: http://eprints.soton.ac.uk/id/eprint/447162
PURE UUID: 5a40c008-6661-4c2f-a47e-bdd0221f61ba
ORCID for Samantha Kanza: ORCID iD orcid.org/0000-0002-4831-9489
ORCID for Jeremy G. Frey: ORCID iD orcid.org/0000-0003-0842-4302
ORCID for Mahesan Niranjan: ORCID iD orcid.org/0000-0001-7021-140X

Catalogue record

Date deposited: 04 Mar 2021 17:39
Last modified: 17 Mar 2024 03:51

Export record

Altmetrics

Contributors

Author: Charlotte Deane
Editor: Samantha Kanza ORCID iD
Editor: Jeremy G. Frey ORCID iD
Editor: Mahesan Niranjan ORCID iD
Editor: Victoria Hooper

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×