Invited Speakers

Brendan Frey, University of Toronto (Canada)
  • Learning deep biological architectures for genomic medicine

Dana Pe'er, Columbia University (USA)
  • A geometric approach to cellular phenotypes.

Matthew Stephens, University of Chicago (USA)
  • False Discovery Rates – a new deal.


Videos of selected talks are available on YouTube. Please click on the titles to watch them.

09:00 AM Learning Deep Biological Architectures for Genomic Medicine
Brendan J Frey
09:45 AM Multi-Tac deep neural network to predict CpG methylation profiles from low-coverage sequencing data
Christof Angermueller
10:05 AM Large-Scale Sentence Clustering from Electronic Health Records for Genetic Associations in Cancer
Stefan Stark
10:10 AM Classifying Microscopy Images Using Convolutional Multiple Instance Learning
Oren Kraus
10:30 AM Basset: Learning the regulatory code of the accessible genome with deep convolutional neural networks
David Kelley
10:50 AM A probabilistic method for quantifying chromatin interactions
Henrik Mannerström
11:35 AM Detecting significant higher-order associations between genotype and phenotype while conditioning on covariates
Laetitia Papaxanthos
11:40 AM Genome-wide modelling of transcription kinetics reveals patterns of RNA production delays
Antti Honkela
11:45 AM Tensor decomposition and causal inference for multi-tissue gene expression experiments
Victoria Hore
11:50 AM Disease mechanism discovery by integrating exome and gene expression datasets in one graphical model of disease
Aziz M Mezlini
02:30 PM Human Traits and Diseases
Dana Pe'er
03:15 PM Bayesian Gaussian Process latent variable models for pseudotime inference in single-cell RNA-seq data
Kieran Campbell
03:35 PM In Silico Design of Synthetic Genes for Total Cell Translation Control: a Multi-output Gaussian Processes approach
Javier Gonzalez