Scientific Program

All talks will take place at Lecture Hall S1-151 - Jean-Coutu Pavilion | Université de Montréal campus.

Tuesday, October 23
08:00Registration & light breakfast
08:45Opening remarks

Session 1

09:00 Keynote: Decoding the human genome with machine learning
Olga Troyanskaya, Princeton University, Princeton, NJ, USA
09:45 Keynote: Deep learning for biomedical applications
Yoshua Bengio, Université de Montréal, Montreal, QC, Canada
10:30 Coffee break
10:50 Panel discussion
12:00 Rapid-fire talk
Predicting canonical and non-canonical box C/D snoRNA interactions
Gabrielle Deschamps-Francoeur, Université de Sherbrooke, Sherbrooke, Canada
12:05 Rapid-fire talk
Prediction of complete Hi-C interaction matrices from sequence-based determinants
Christopher Cameron, School of Computer Science, McGill University, Montreal, QC, Canada
12:10 Rapid-fire talk
Unravelling tumor heterogeneity in TNBC along the course of treatment through single-cell RNA-seq
Yang Yang, Department of Human Genetics, McGill University, Montreal, QC, Canada
12:15 Lunch
13:15 Poster session

Session 2

14:15 Applications of Deep Learning in Medicine: Imaging and Genomics
Joseph Paul Cohen, Université de Montréal, Montreal, QC, Canada
15:00 Machine learning for medical diagnostic and prognostic: reality and fiction
Jacques Corbeil , CRCHU de Québec - Université Laval, Quebec City, QC, Canada
15:45 Coffee break
16:10 A cancer precision medicine program driven by multi-omics, analytics and modeling
Olivier Elemento, Cornell University, Ithaca, NY, USA
16:55 Development of gene expression signatures, insights from applications
Sébastien Lemieux, IRIC - Université de Montréal, Montreal, QC, Canada
17:40 Cocktail

Wednesday, October 24
08:15Light breakfast

Session 3

09:00 Accelerating bio discovery with machine learning
Lucy Colwell, Google LLC, Mountain View, CA, USA
09:45 MD + Machine: Machine Learning in Computer-Assisted Diagnosis and Interventions
Parvin Mousavi, Queen's University, Kingston, ON, Canada
10:30 Coffee break
10:50 Translational Radiomics for Precision Medicine for Cancer: Opportunities and Challenges
Farzad Khalvati, LTRI - University of Toronto, Toronto, TO, Canada
11:30 Invited abstract
The gene signature fallacy: the necessity for a highly polygenic model
Assya Trofimov, IRIC - Université de Montréal, Montreal, QC, Canada
11:45 Invited abstract
Better decoding of TF signals in accessible chromatin with learned embeddings and neural networks
Lee Zamparo, Memorial Sloan Kettering Cancer Center, New York, NY, USA
12:00 Rapid-fire talk
miRBooking 2.0: An Enzymatic Model for the Microtargetome
Guillaume Poirier-Morency, Département d'informatique et de recherche opérationelle, Université de Montréal, Montreal, QC, Canada
12:05 Rapid-fire talk
Fooling the classifier: adversarial examples and ligand antagonism
Thomas Rademaker, Department of Physics, McGill University, Montreal, QC, Canada
12:10 Rapid-fire talk
Conditional Approximate Bayesian Computation, a new approach for across-site dependency in high-dimensional mutation-selection models
Simon Laurin-Lemay, Department of Biochemistry and Molecular Medicine, Faculty of Medicine, Université de Montréal, Montreal, QC, Canada
12:15 Lunch 13:15 Poster session

Session 4

14:15 Predictive models of cancer progression and prognosis from RNA processing patterns
Eduardo Eyras, Pompeu Fabra University, Barcelona, Spain
15:00 Invited abstract
Phylogenetic Manifold Regularization: A Semi-Supervised Approach for Transcription Factor Binding Sites Prediction
Faizy Ahsan, School of Computer Science, McGill University, Montreal, QC, Canada
15:15 Invited abstract
Towards Gene Expression Convolutions using Gene Interaction Graphs
Martin Weiss, Montreal Institute for Learning Algorithms, Université de Montréal, Montreal, QC, Canada
15:30 Invited abstract
Study of Population Admixture with Diet Networks
Léo Choinière, Montreal Heart Institute, Faculty of Medicine, Université de Montréal, Montreal, QC, Canada
15:50 Coffee break
16:10 Clonal evolution in cell lines and patient derived xenografts investigated with scalable whole genome single cell sequencing
Andrew McPherson, Senior Postdoctoral Fellow, Sohrab Shah Lab
Memorial Sloan Kettering Cancer Center, New York, NY, USA
16:55 Machine learning: from (epi)genetics to gene editing to protein optimization
Jennifer Listgarten, UC Berkeley, Berkeley, CA, USA
17:40 Closing remarks