MLCB - Schedule

5pm - Poster session and reception

5:20 - 6:10 pm - Keynote speech, Quaid Morris - University of Toronto (Canada) "How to be a machine learning biologist" (details here)

6:10 pm - 8 pm - Poster session (details here)

8:50 - 9 am Introduction

9 - 9:10 am Travel award announcement (sponsor: Recursion)

9:10 - 9:55 am Keynote speech, Daphne Koller - Insitro (USA) "Machine learning: A new approach to drug discovery" (details here)

9:55 - 11 am Oral session I (details here)

Learning, using, and extending variational distributions of phylogenetic trees
Deep Multiple Instance Learning for Taxonomic Classification of Metagenomic read sets
Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting
Reconstructing continuous distributions of 3D protein structure from cryo-EM images

11 - 11:30 am Spotlight presentations (details here)

11:30 - 1:30 pm Lunch + poster session (details here)

1:30 - 2:15 pm Keynote Speech, Jennifer Listgarten - UC Berkeley (USA) "Machine learning for protein engineering" (details here)

2:15 - 3 pm Oral session II (details here)

Pre-Training of Deep Bidirectional Protein Sequence Representations with Structural Information
Energy-based models for atomic-resolution protein conformations
Protein Fold Recognition with Recurrent Kernel Networks

3 - 3:20 pm Coffee break

3:20 - 4:05 pm Keynote speech, William Stafford Noble - University of Washington (USA) "Machine learning methods for making sense of big genomic and proteomic data" (details here)

4:05 - 4:50 pm Oral session III (details here)

Deep exploration networks for rapid engineering of functional DNA sequences
Efficient variance components analysis across millions of genomes
Cross-species Transcription Factor Binding Prediction via Domain-adaptive Neural Networks

4:50 - 5 pm Closing remarks