Day 1 of the symposium will focus on machine learning applications in precision medicine, while day 2 will focus on genomics and will double as the regular meeting of the North England Genetical Epidemiology Group (NEGEG). Everyone is welcome to attend both days; however, if you plan to only attend one of the days, we ask that you let us know so that we can make additional tickets available for people wishing to attend the other day.
Tuesday 25th June (Day 1) – Machine Learning for Precision Medicine
9.00-9.30am: Arrival and Registration
9.30-10.15am: Neural decomposition models. Chris Yau. Institute of Cancer and Genomic Sciences, University of Birmingham.
10.15-10.45am: Tea break
10.45-11.40pm: Contributed session 1
10.45-11.10am: Identifying microRNAs as biomarkers in pulmonary arterial hypertension. Niamh Errington, James Iremonger, Christopher Rhodes, Alexander Mk Rothman, Robin Condliffe, Charles A Elliot, David G Kiely, Luke S Howard, John Wharton, Martin Wilkins, Allan Lawrie and Dennis Wang.
11.15-11.40am: Machine learning of whole-blood gene expression to uncover IPAH heterogeneity. Sokratis Kariotis, Allan Lawrie and Dennis Wang.
11.45-12.15pm: Ice-breaker networking session
1.15-2pm: Genomics, data and drug discovery. John Whittaker, Vice President, Human Genetics at Glaxo Smith Kline Pharmaceuticals
2-2.45pm: Applying Instrumental Variable methods to identify multiple treatment effect parameters in RCTs: lessons from genetic epidemiology. Jack Bowden. MRC Integrative Epidemiology Unit, University of Bristol.
2.45-3.40pm: Contributed session 2
2.45-3.10pm: Genetic Risk Prediction with Artificial Neural Networks. Carlos Pinto, Michael Gill and Elizabeth Heron.
3.15-3.40pm: Sparse variable selection and covariance selection in Seemingly Unrelated Regressions and Structural Equation Models. Alex Lewin.
3.45-4.15pm: Tea break
4.15-5pm: Machine learning and medicine: Where do we stand and where are we going? Sach Mukherjee, German Centre for Neurodegenerative Diseases (DZNE).
Wednesday 26th June (Day 2) – Statistical Genomics and NEGEG Meeting
9.30-10.25am: Contributed session 3
9.30-9.55am: Identifying genomic regions susceptible to systematic sequencing error to improve variant detection. Timothy Freeman, Jason Harris and Dennis Wang.
10-10.25am: Tree-based transcriptome wide association studies in autoimmune diseases. Nastasiya Grinberg and Chris Wallace.
10.30-11am: Tea break
11-11.55am: MR-pheWAS using PHESANT: systematically evaluating causal effects on thousands of outcomes in UK Biobank. Louise Millard, MRC Integrative Epidemiology Unit, University of Bristol.
12-12.30pm: Networking Session
1.30-2.15pm: Machine learning for early prediction of circulatory failure in the intensive care unit. Stephanie Hyland, Biomedical Informatics, Cambridge University.
2.15-2.40pm: Contributed session 4
2.15-2.40pm: Detecting Epistasis by Interpreting Black Box Models. Jonathan Ish-Horowicz, Seth Flaxman and Sarah Filippi.
2.45-3.15pm: Tea break
3.15-4pm: Prediction of treatment response in Rheumatoid Arthritis patients using genome-wide SNP data. Svetlana Cherlin, Newcastle Clinical Trials Unit, Newcastle University.