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RSG with DREAM 2020 | November 16-19, 2020 |Conference Programme

Oral Presentations Schedule

Programme Schedule tentative and subject to change. 
Programming time is Eastern Standard Time.

RSG Schedule

Monday – Day 1 – November 16, 2019
Go directly to: Tuesday, Nov 17Wednesday, Nov 18 (DREAM)Thursday, Nov 19 (DREAM)
10:00 am 10:05 am Welcome and Intro
10:05 am 10:50 am Keynote - Su-In Lee
Explainable Artificial Intelligence for Biology and Health
10:50 am 11:50 am Complex Molecular Interactions
  • Mapping cell structure across scales by fusing protein images and interactions - Yue Qin
  • A Network-based comparative framework to study conservation and divergence of proteomes in plant phylogenies - Junha Shin
  • Mapping gene regulatory networks in the Drosophila brain using single-cell transcriptomics and epigenomics - Sara Aibar
  • Identifying diverse modes of TF-DNA interactions in ChIP-exo data - Anushua Biswas
11:50 am 12:30 pm Break
12:30 pm 1:15 pm Special Session Keynote - Sara Mostafavi
Machine Learning for extracting meaningful patterns in large genomics datasets
1:15 pm 2:15 pm Special Session on Regulatory and Systems Genomics in Immunology
  • Integrated multi-omics approach to identifying regulatory mechanisms in cancer metastatic processes - Saba Ghaffari
  • Varmole: A biologically drop-connect deep neural network model for prioritizing disease risk variants and genes - Nam Nguyen
  • Inferring cellular trajectories from scRNA-seq in pseudospace - Aly Khan
  • Inferring the pan-cancer interactions and prognostic significance of driver mutations and the tumor immune microenvironment - Masroor Bayati
2:15 pm 3:00 pm Special Session Keynote - Harinder Singh
Genomic Regulatory Codes and Transcriptional Circuits Controlling Mammalian Cell States and their Dynamics
3:00 pm 4:00 pm Posters
Tuesday – Day 2 – November 17, 2019
Go directly to: Monday, Nov 16Wednesday, Nov 18 (DREAM)Thursday, Nov 19 (DREAM)
    Open Poster Viewing
10:00 am 10:05 am Welcome and Intro
10:05 am 10:50 am Keynote - Brenda Andrews
Systematic genetic perturbation screens to map biological networks
10:50 am 11:50 am Single Cell Analysis
  • SPICEMIX: Integrative single-cell spatial modeling for inferring cell identity - Benjamin Chidester
  • Chromatin accessibility and transcription factor activity estimation on single cells - Ivan G. Costa
  • Mapping vector field of single cells - Yan Zhang
  • Developmental trajectory of pre-hematopoietic stem cell formation from endothelium - Qin Zhu
11:50 am 12:30 pm Break
12:30 pm 1:15 pm Keynote - Ziv Bar-Joseph
Reconstructing dynamic regulatory networks from time series single cell data
1:15 pm 2:15 pm From Sequence to Function
  • Ledidi: Designing genome edits that induce functional activity - Jacob Schreiber
  • Genome-wide identification and analysis of RNA structural disruptions induced by single nucleotide variants - Zhengqing Ouyang
  • Neural Networks Can Extract Thermodynamic DNA Sequence Affinities from Genomic Occupancy Profiles of Transcription Factor Binding - Amr Alexandari
  • Assessing the enrichment of somatic mutations in TF binding sites - Harshit Sahay
2:15 pm 3:00 pm Keynote - Elaine Mardis
Pediatric CNS Cancers:  Exploring Clinical Data to Inform Treatment
3:00 pm 4:00 pm Networking

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DREAM Schedule

Wednesday - Day 3 – November 18, 2020
Go directly to: Monday, Nov 16Tuesday, Nov 17Thursday, Nov 19 (DREAM)
10:00 am 10:10 am Welcome and Introductory Remarks from Pablo Meyer
10:10 am 10:50 am Keynote - Rada Mihalcea
Language as a Window into Human Behavior: A Computational Perspective
10:50 am 11:40 am Preterm Birth Prediction: Transcriptomics DREAM Challenge
Session Chair
- James Costello
  • Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth - Adi Tarca 
  • Dealing with high dimensional data to predict preterm birth - Balint A. Pataki and Istvan Csabai (Team ELTEcomplex) 
  • Omics-based prediction of preterm birth by Gaussian Process Regression models - Yuanfang Guan (Team gyuanfan)
  • SVM-based approach to predict preterm birth using omics data - Rintu Kutum (Team rABiT)
11:40 am 12:10 pm Metadata Automation DREAM challenge
Session Chair
- Thomas Schaffer
  • Metadata Automation DREAM Challenge - Denise Warzel
  • Biomedical Analysis of Composite Ontological Networks - Lauren Cirillo (Team ENGR Dynamics)
  • An Iterative Strategy Optimizing CDE Recommendations from Real-World Data - Attila L. Egyedi (Team CEDAR Team)
  • Metadata Automation: A TF-IDF and Nearest Neighbors Approach - Emily Hartley (Team )
12:10 pm 12:40 pm Lunch Break
12:40 pm 1:30 pm CTD2 Pancancer Drug Activity DREAM Challenge
Session Chair
- Robert Allaway
  • CTD2 Pancancer Drug Activity DREAM Challenge - Robert Allaway & Eugene Douglass
  • Predicting drug targets by integration of drug sensitivity data and drug gene signature data - the NETPHAR strategy - Wenyu Wang (Team netphar)
  • A multitask neural network approach for predicting drug targets from chemogenomics data - Fangping Wang (Team Atom)
1:30 pm 1:40 pm Break
1:40 pm 2:30 pm RA2 DREAM Challenge: Automated Scoring of Radiographic Joint Damage
Session Chair - Jim Costello
  • Introduction to the RA2 DREAM Challenge: Automated Scoring of Radiographic Joint Damage - Lou Bridges
  • Scoring and benchmarking for the RA2 DREAM Challenge - Jake Chen
  • Prediction of Rheumatoid Arthritis Scores Ariel's Method (PRASAM) - Ariel Israel
  • A multistage deep learning method for scoring radiographic hand and foot joint damage in rheumatoid arthritis - Isaac Dimitrovsky
  • Li and Guan RA2 DREAM Challenge Solution - Hongyang Li
  • Team Csabaibio RA2 DREAM Challenge Solution - Alex Olar
2:30 pm 3:30 pm Posters
Thursday - Day 4 – November 19, 2020
Go directly to: Monday, Nov 16Tuesday, Nov 17Wednesday, Nov 18 (DREAM)
10:00 am 10:10 am Welcome and Introductory Remarks
Pablo Meyer
10:10 am 10:50 am Keynote - Dina Machuve
Poultry Diseases Diagnostics using Deep Learning
10:50 am 11:40 am CTD2 Beat AML DREAM Challenge
Session Chair
- Brian White
  • CTD2 Beat AML DREAM Challenge: Strategies for Prediction of Drug Efficacy and Patient Outcomes - Jeff Tyner
  • Prediction of drug sensitivity using a multi-response model - Rasmus Froberg Brøndum
  • Beat AML SC2: Predicting clinical response using feature selection for survival analysis - Yasin Memari
11:40 am 12:25 pm BEAT-PD DREAM Challenge
Session Chair
- Solveig Sieberts
  • Parkinson's disease symptom assessment in free-living conditions; the BEAT-PD Challenge - Solveig Sieberts
  • Personalized prediction of on-off medication state from wearable-derived time-series features - Yidi Huang
  • Assessment of Parkinson's disease dyskinesia in a free-living environment - Alex Page
  • Tremor severity in Parkinson’s disease can be monitored in a free-living environment - Yuanfang Guan
12:25 pm 12:55 pm Lunch Break
12:55 pm 1:30 pm The EHR Challenges (The COVID-19 EHR DREAM Challenge and the EHR DREAM Challenge)
Session Chair
- Justin Guinney
  • The First EHR DREAM Challenge: overcoming data access barriers in biomedical competitions - Thomas Schaffter and Tim Bergquist
  • A LightGBM Model to Predict 180 Days Mortality Using EHR Data - Jifan Gao  (Team UW-biostat)
1:30 pm 2:00 pm The Future of DREAM
Justin Guinney
2:00 pm 3:00 pm Networking

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