Session 1: Chair: Wesley Tansey

8:30 - 8:40 Opening remarks

8:40 - 9:20 Invited Talk: Jean-Philippe Vert

9:20 - 9:40 Contributed Talk:

Inferring Multi-Dimensional Rates of Aging from Cross-Sectional Data, Emma Pierson, Pang Wei Koh, Tatsunori Hashimoto, Daphne Koller, Jure Leskovec, Nick Eriksson and Percy Liang

9:40 - 9:45 Paper Highlight:

Selective Classification via Curve Optimization, Avanti Shrikumar, Amr Alexandari and Anshul Kundaje

9:45 - 10:00 Spotlights Set 1:

Continuous embeddings of DNA sequencing reads and application to metagenomics, Romain Menegaux and Jean-Philippe Vert

Toward an Alignment-Free Method for Feature Extraction and Accurate Classification of Viral Sequences, Dylan Lebatteux, Mohamed Amine Remita and Abdoulaye Baniré Diallo

Linkage-Disequilibrium Regularized Support Vector Machines for Genome-Wide Association Studies, Mukund Sudarshan and Lakshmi Subramanian

10:00 -10:30 Poster Session & Coffee Break

Session 2: Chair: Abdoulaye Baniré Diallo

10:30 - 11:10 Invited Talk: Samuel Kaski

11:10 - 11:30 Contributed Talk:

Attentive cross-modal paratope prediction, Andreea Deac, Petar Veličković and Pietro Sormanni

11:30 - 12:30 Poster session

12:30 - 2:00 Lunch break

Session 3:

Chair: Elham Azizi

2:00 -2:40 Invited Talk: Dana Pe’er

2:40 - 3:00 Contributed Talk:

DECODER: A probabilistic approach to integrate big data reveals mitochondrial Complex I as a potential Alzheimer’s disease therapeutic target,

Safiye Celik, Josh C Russell, Cezar R Pestana, Ting-I Lee, Shubhabrata Mukherjee, Paul K Crane, Dirk Keene, Jennifer F Bobb, Matt Kaeberlein and Su-In Lee

3:00 - 3:15 Spotlight Set 2:

Regularization Learning Networks, Ira Shavitt and Eran Segal

Compositional modeling of core splicing regulation improves prediction of variant effects on splicing, Jun Cheng, Nguyen Thi Yen Duong, Ziga Avsec and Julien Gagneur

Auto-Encoding Topographic Factors, Antonio Moretti, Andrew Stirn and Itsik Pe'er

3:15 - 4:00 Poster Session & Coffee Break

Session 4:

Chair: Sandhya Prabhakaran

4:00 - 4:20 Contributed Talk:

scLL-LVM: Bayesian Manifold Learning for Single-Cell Gene Expression Data, Cassandra Burdziak, Mervin Fansler and Dana Pe'er

4:20 - 5:20 Poster session

5:20 - 5:30 Award Ceremony & Closing Remarks