Schedule
Date: Friday, June 14, 2019
Location: 101, Level 1, Promenade 100, Convention center, Long Beach, CA, USA
Session 1:
Chair: Elham Azizi
8:30 - 8:40 Opening remarks
8:40 - 9:20 Invited Talk: Caroline Uhler, Associate Professor, EECS and Institute for Data, Systems and Society, MIT: "From Single Cell Measurements to Computational Models of Gene Networks and 3D DNA Organization"
9:20 - 9:50 Paper Highlights:
- Jacopo Cirrone: Network Walking charts transcriptional dynamics of nitrogen signaling by integrating validated and predicted genome-wide interactions
- Marttinen Pekka: A Bayesian model of acquisition and clearance of bacterial colonization incorporating within-host variation
- Elior Rahmani: A Bayesian framework for estimating cell-type composition from DNA methylation without the need for methylation reference
- Elior Rahmani: Cell-type-specific resolution epigenetics without the need for cell sorting or single-cell biology
- Harri Lähdesmäki: An additive Gaussian process regression model for interpretable probabilistic non-parametric analysis of longitudinal data
9:50 - 10:10 Contributed Talk 1: Ali Oskooei: Network-based Biased Tree Ensembles (NetBiTE) for Drug Sensitivity Prediction and Drug Sensitivity Biomarker Identification in Cancer
10:10 - 11:00 Poster Session & Coffee Break
Session 2:
Chair: Cassandra Burdziak
11:00 - 11:40 Invited Talk: Francisco LePort, Co-founder and CEO at Gordian Biotechnology : "Gordian Biotechnology: Exploring the in vivo perturbome"
11:40 - 12:00 Spotlight Set 1:
- Ali Oskooei: Towards Explainable Anticancer Compound Sensitivity Prediction via Multimodal Attention-based Convolutional Encoders
- Zhenqin Wu: PB-Net: Automatic Peak Integration by Sequential Deep Learning for Multiple Reaction Monitoring
- Jimeng Sun: MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals
- Karren Dai Yang: Multi-Domain Translation by Learning Uncoupled Autoencoders
- Mijung Kim: Towards Diagnosis of Rotator Cuff Tears in 3-D MRI Using 3-D Convolutional Neural Networks
12:00 - 2:00 Poster Session & Lunch break
Session 3:
Chair: Cassandra Burdziak
2:00 - 2:20 Contributed Talk 2: Trung, Ngo Trong: SISUA: SemI-SUpervised generative Autoencoder for single cell data
2:20 - 2:50 Spotlight Set 2:
- Achille Nazaret: A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements
- François Fages: A Statistical Learning Algorithm for Inferring Reaction Networks from Time Series Data
- Brandon Carter: Critiquing Protein Family Classification Models Using Sufficient Input Subsets
- Ruishan Liu: Inferring Single-cell Trajectory, Pseudo-time and Gene Regulation Using RNA Velocity
- Nicasia Beebe-Wang: MD-AD: Multi-task deep learning for Alzheimer's disease neuropathology
2:50 - 4:00 Poster Session & Coffee Break
Session 4:
Chair: Sandhya Prabhakaran
4:00 - 4:40 Invited Talk: Daphne Koller, Founder and CEO, insitro; Co-founder, Coursera; Adjunct Professor of Computer Science and Pathology, Stanford University: "Machine learning: A new approach to drug discovery"
4:40 - 5:00 Contributed Talk 3: Bryan He: Predicting Tumor Mutation Burden from Histopathology Images Using Multiscale Deep Learning
5:00 - 5:15 Award Ceremony & Closing Remarks