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LeedsOmics seminar series 2018-2019

 

Timetable

Date Time Venue Host Speaker Affiliation Title
Monday 22nd October 2018 15:00 – 16:00 Worsley SR (9.60) - - - Welcome event
Monday 5th November 2018 15:00 – 16:00 Roger Stevens LT 02 (7M.02) Julie Aspden/Niamh Forde Jeanine Houwing-Duistermaat University of Leeds Dimension reduction methods for multiple omics datasets
Monday 26th November 2018 15:00 – 16:00 Roger Stevens LT 02 (7M.02) Julie Aspden/Niamh Forde Frank Sobott University of Leeds Native MS and Structural Proteomics @Leeds
Monday 3rd December 2018 15:00 – 16:00 Roger Stevens LT 23 (8.23) Simon Goodman Professor AR Hoelzel Durham University Adaptation and drift in the deep sea
Monday 21st January 2019 15:00 – 16:00 Roger Stevens LT 16 (12.16) David Westhead Magnus Rattray University of Manchester Using Gaussian processes to model branching dynamics from single-cell data
Monday 4th February 2019 15:00 – 16:00 Worsley SR (8.43Y) Megan Wright Kathryn Lilley University of Cambridge Capturing the spatial organisation of the transcriptome and proteome
Monday 18th February 2019 15:00 – 16:00 Worsley SR (8.43X) Richard Cubbon Tom Webb University of Leicester Understanding the genetic causes of coronary artery disease
Monday 4th March 2019 15:00 – 16:00 Roger Stevens LT 19 (10.19) Martin Callaghan Hatem Nawar Google Pushing the boundaries of what is possible in bioinformatics and medicine with Google Cloud, Big Data and Artificial Intelligence
Thursday 28th March 2019 15:00 – 16:00 Roger Stevens LT 06 (8.06) James Thorne Luca Magnani Imperial College London Diving into the dark matter of the breast cancer genome
Wednesday 10th April 2019 14:00 – 15:00 Roger Stevens LT 08 (9.08) Paolo Actis Jean Francois Masson Université de Montreal Plasmonic nanobiosensors: From therapeutic drug and environmental monitoring to optophysiology of living cells
Monday 29th April 2019 15:00 – 16:00 Roger Stevens LT 13 (10.13) Paolo Actis Iain Macaulay Earlham Institute Detail vs. scale in single cell genomics: different approaches to get the data you need from a single cell