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ISCB - A Safe Space (Code of Conduct)

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DREAM Posters Schedule
DREAM Posters -
Go directly to: RSG Posters
#	Author(s)	Title
D1	Pratheepa Jeganathan, Anne-maud Ferreira, Jathushan Rajasegaran, Susan Holmes	Predicting Gestational Age Using Transcriptomic data
D2	HaoYang Zhang, Hanhui Li, Mingpeng Zhao, Yuedong Yang	A fusion model to predict gestational age prediction by integrating blood gene expression data
D3	Harpreet Kaur, Sumeet Patiyal, Anjali Dhall, Neelam Sharma, Gajendra Raghava	Preterm Birth prediction from the Gene-expression profiles of Pregnant Women using Machine Learning Techniques
D4	Hyelim Jung, Dawoon Leem, Hyungyu Lee, Woong Jeong, Junyoung Park, Bogyu Park	Ensemble Regression Method for Prediction Gestational Age
D5	Houriiyah Tegally, Malawi Kiran Anmol, Shakuntala Baichoo	Using computational modelling to predict Artemisinin drug resistance from Plasmodium transcriptomics data for improved malaria therapeutics
D6	Nicola Lawford, Jonathan Chan, Narumol Noungpan, Worrawat Engchuan	Functional Pathway-Based Feature Transformation of \textit{P. falciparum} Gene Expression Data for Artemisinin Resistance Prediction
D7	Monica Gomez Orozco, Jahir Guitierrez Bugarin	Kernel Ridge Regression and Voting XGBoost Models for Prediction of Artemisin Resistance in P. falciparium parasites
D8	Colby Ford	Ensemble Machine Learning Modeling for the Prediction of Artemisinin Resistance in Malaria
D9	Jovan Tanevski, Thin Nguyen, Buu Truong, Nikos Karaiskos, Mehmet Eren Ahsen, Xinyu Zhang, Chang Shu, Ke Xu, Xiaoyu Liang, Ying Hu, Hoang V.V. Pham, Li Xiaomei, Thuc D. Le, Adi L. Tarca, Gaurav Bhatti, Roberto Romero, Nestoras Karathanasis, Phillipe Loher, Yang Chen, Zhengqing Ouyang, Disheng Mao, Yuping Zhang, Maryam Zand, Jianhua Ruan, Christoph Hafemeister, Peng Qiu, Duc Tran, Thin Nguyen, Attila Gabor, Thomas Yu, Enrico Glaab, Roland Krause, Peter Banda, Dream Sctc Consortium, Gustavo Stolovitzky, Nikolaus Rajewsky, Julio Saez-Rodriguez and Pablo Meyer	Predicting cellular position in the Drosophila embryo from Single-Cell Transcriptomics data
D10	Adi Tarca	Preterm Birth Prediction: Transcriptomics Challenge Overview Talk

RSG Posters Schedule
RSG Posters -
Go directly to: DREAM Posters
#	Author(s)	Title
1	Lautaro Soler	Image processing on the brain: 3D printing MRI images for further observation
2	Jia-Ying Su, En-Yu Lai, Chun-Houh Chen and Yen-Tsung Huang	Visualization for high-dimensional mediation effects (HDMV) with application to (epi)genome-wide mediation
3	Muhammad Muzammal Adeel	VARIATION OF THE 3D GENOME ARCHITECTURE IN CERVICAL CANCER DEVELOPMENT
4	Rania Hassan, Nourhan Abu-Shahba, Marwa Mahmoud, Ahmed M. H. Abdel-Fattah, Wael Zakaria and Mahmoud Elhefnawi	Co-regulatory Network of Oncosuppressor miRNAs and Transcription Factors for Pathology of Human Hepatic Cancer Stem Cells (HCSC)
5	Niels Nguedia Kaze, Wilfred Mbacham and Jean Paul Chedjou	CHARACTERIZATION OF 331G/A POLYMORPHISM OF RP GENE AND IDENTIFICATION OF VIRAL ONCOGENE HMTV VIRUS AS GENETIC MARKERS FOR THE IMPROVEMENT OF BREAST CANCER MANAGEMENT IN CAMEROON
6	Rohit Arora, Harry M. Burke and Ramy Arnaout	Immunological Diversity with Similarity
7	Qian Li, Hemang Parikh, Martha Butterworth, Åke Lernmark, William Hagopian, Marian Rewers, Jin-Xiong She, Jorma Toppari, Anette-G. Ziegler, Beena Akolkar, Oliver Fiehn, Sili Fan and Jeffrey Krischer	Longitudinal metabolome-wide signals prior to the appearance of pancreatic islet autoantibodies in children at genetic risk for type 1 diabetes: the TEDDY study
8	Eleonora Achrak, Jennifer Fred, Jessica Schulman	Unlocking the glow: characterize of bioluminescent genes in fireworm Odontosyllis enopla
9	Siddharth Krishnakumar	VCFDataPy: A Software tool to analyze human genome variation data to discover chromosomal abnormalities in Autism and other genetic brain disorders.
10	Kiley Graim and Olga Troyanskaya	Time-series gene interaction networks of fetal brain development predict genetic drivers of neurodevelopmental disorders
11	Weizhong Li	Combined alignments of sequences and domains characterize unknown proteins with remotely related protein search PSISearch2D
12	Olaitan Awe, Angela Makolo, Segun Fatumo	Computational Genomic Analysis of Bacteriophages in Typhoidal Salmonella Sequences
13	Douglas Phanstiel	Visualizing data within the context of human kinase, phosphatase, and transcription factor families
14	Amartya Singh, Hossein Khiabanian and Gyan Bhanot	Tunable biclustering algorithm for integrative analysis of tumor transcriptomic and epigenomic data
15	Bobbie-Jo Webb-Robertson, Lisa Bramer, Bryan Stanfill, Sarah Reehl, Ernesto Nakayasu, Thomas Metz, Brigitte Frohnert, Jill Norris, Randi Johnson, Stephen Rich and Marian Rewers	Discovery of Disparate Biological Features Predicting Islet Autoantibodies via Integrated Machine Learning Feature Selection
16	Avyay Varadarajan, Avanti Shrikumar and Anshul Kundaje	Using Deep Learning to Understand the Sequence Determinants of CTCF Binding from CUT&RUN data
17	Tarun Chiruvolu, Avanti Shrikumar, Daniel Kim and Anshul Kundaje	A Computational Dissection of Genome-Wide Transcription Factor Binding Sites Using Deep Learning Models of Chromatin Accessibility in Skin Differentiation
18	Nicole Kramer and Douglas Phanstiel	BentoBox.R: customizable plotting and arranging of genomic data sets using R grid Graphics
19	Kenny Ye Liang, Feng Bao, Yue Deng and Qionghai Dai	Fast and scalable identification of rare cell subpopulations from large-scale single-cell transcriptomics
20	Vu Viet Hoang Pham, Lin Liu, Cameron Bracken, Gregory Goodall, Qi Long, Jiuyong Li and Thuc Duy Le	Methods for identifying single and group-based coding/non-coding cancer drivers
21	Joshua Wetzel, Mona Singh	Inferring DNA-binding specificities jointly across structurally similar proteins
22	Hannah Zhou, Avanti Shrikumar and Anshul Kundaje	A head-to-head benchmarking of reverse-complement-aware architectures for genomics
23	Chen Su, William Pastor and Amin Emad	An integrative approach for identification of lineage-relevant transcriptional regulatory networks in human embryogenesis
24	Jennifer Ferd, Trami Dang, Eleonora Achrak, Jessica Schulman, Konstantinos Krampis, Mande Holford	Developing a bioinformatics pipeline for characterizing venom peptides from terebrid snails
25	Eileen Li, Avanti Shrikumar, Georgi Marinov, Connor Horton, Polly Fordyce and Anshul Kundaje	Training and interpreting a deep learning model to understand the fine-grained sequence determinants of Pho4 binding from high-resolution PB-exo data
26	Joonas Tuominen, Ebrahim Afyounian, Francesco Tabaro, Tomi Häkkinen, Anastasia Shcherban, Matti Annala, Riikka Nurminen, Kati Kivinummi, Teuvo Tammela, Alfonso Urbanucci, Leena Latonen, Juha Kesseli, Kirsi Granberg, Tapio Visakorpi and Matti Nykter	Chromatin accessibility in human prostate cancer progression
27	Sungjoon Park, Minji Jeon, Sunkyu Kim, Junhyun Lee, Seongjun Yun, Bumsoo Kim, Buru Chang and Jaewoo Kang	In Silico Molecular Binding Affinity Prediction with Multi-Task Graph Neural Networks
28	Chris Jackson, David Gresham and Richard Bonneau	Gene regulatory network reconstruction using single-cell RNA sequencing of barcoded genotypes in diverse environments
29	Christopher Magnano and Anthony Gitter	Automating parameter selection to avoid implausible biological pathway models
30	Emily Ackerman, Ericka Mochan and Jason Shoemaker	Mathematical Model of the Strain-Specific Immune Response to Influenza Virus
31	Anjun Ma, Cankun Wang, Yuzhou Chang and Qin Ma	Identification of cell-type-specific alternative regulons from single-cell RNA-Seq
32	Mervin Fansler, Gang Zhen and Christine Mayr	3’ UTR isoform usage is cell type-specific and switches during differentiation predominantly in genes without expression changes
33	Qian Zhu, Ruben Dries, Chee-Huat Linus Eng, Arpan Sarkar, Feng Bao, Rani George, Nico Pierson, Long Cai and Guo-Cheng Yuan	Giotto, a pipeline for integrative analysis and visualization of single-cell spatial transcriptomic data
34	Qian Zhu, Nan Liu, Stuart Orkin and Guo-Cheng Yuan	CUT&RUNTools: a flexible pipeline for CUT&RUN processing and footprint analysis
35	Gabrielle Perron and Hamed Shateri Najafabadi	A unified framework for comparing ratios in sequencing count data
36	Rachel Hovde, Gus Zeiner, Jay Danao, Charlotte Davis, Melissa Fardy, Nicole Grant, Dianna Lester-Zeiner, David Mai, Krista McNally, Michon Pinnix, Erin Riegler, Daniel Roche and Ben Wang	A new approach to arm T cell therapies with conditional, transgenic payload outputs
37	Merve Sahin, Mark Carty, Lee Zamparo and Christina Leslie	HiC-DC+: A Robust Statistical Tool to Detect Significant Interactions from Hi-C, HiChIP and CHiC data
38	Erik Ladewig, Eneda Toska and Maurizio Scaltriti	PI3K pathway mediated splicing defects in ER+ breast cancer.
39	Vincentius Martin, Farica Zhuang and Raluca Gordân	Cooperative binding of transcription factors to clusters of DNA binding sites
40	Joseph Wayman, Diep Nguyen, Peter DeWeirdt, Tareian Cazares, Bryan Bryson and Emily Miraldi	Gene regulatory network inference from single-cell RNA-seq uncovers transcriptional programs controlling human macrophages
41	Cynthia Ma and Michael R. Brent	Transcription Factor Activity Inference: Does it really work?
42	Osama Arshad, Vincent Danna, Vladislav Petyuk, Paul Piehowski, Tao Liu, Karin Rodland and Jason McDermott	An Integrative Analysis of Tumor Proteomic and Phosphoproteomic Profiles to Examine the Relationships Between Kinase Activity and Phosphorylation
43	Ziynet Nesibe Kesimoglu and Serdar Bozdag	Inferring competing endogenous RNA (ceRNA) interactions in cancer
44	Matthew Stone, Sunnie Grace McCalla, Viswesh Periyasamy, Alireza Fotuhi Siahpirani and Sushmita Roy	Benchmarking regulatory network inference algorithms for single-cell RNA-sequencing datasets
45	Joost Groot, Catherine Nezich, Eric Marshall, Anne Campbell, Patrick Cullen, Chao Sun and Warren Hirst	An RNA-Seq approach to translate gene and pathway impacts of cellular clearance activator TFEB for drug discovery in Parkinson’s Disease
46	Roger Pique-Regi, Roberto Romero, Adi Tarca, Edward Sendler, Yi Xu, Valeria Garcia-Flores, Yaozhu Leng, Francesca Luca, Sonia Hassan and Nardhy Gomez-Lopez	Single Cell Analysis of the Human Placenta Transcriptome in Parturition
47	Antonina Mitrofanova, Nusrat Epsi, Sukanya Panja and Sharon Pine	pathCHEMO: a generalizable computational framework to uncover molecular pathways of chemoresistance in lung adenocarcinoma
48	Justyna Resztak, Julong Wei, Peijun Wu, Shiquan Sun, Edward Sendler, Adnan Alazizi, Henriette Mair-Meijers, Allison Farrell, Richard Slatcher, Samuele Zilioli, Xiang Zhou, Francesca Luca and Roger Pique-Regi	Genetics of gene expression response in asthma at single cell resolution
49	Wei Zhang and Jiao Sun	Network-based Learning Methods to Explore the Role of Post-Transcriptional Regulation in Cancer
50	Irem Celen and Robert Kueffner	Gene and domain specific interpretation of missense variant pathogenicity prediction
51	Nidia E. BeltrÁn HernÁndez and Heriberto Manuel Rivera	The role of Voltage-Gated Ion Channels Subunits in Osteosarcoma Metastasis
52	Faiz Rizvi, Tariean Cazares, Iyer Balaji, Matt Weirauch, Leah Kottyan, Surya Prasath and Emily R. Miraldi	Using Deep Learning to Predict Cell Type-specific Chromatin Accessibility Based on Genotype Alone
53	Mariano I. Gabitto, Anders Rasmussen, Orly Wapinski, Kathryn Allaway, Nicholas Carriero, Gordon J. Fishell and Richard Bonneau	Characterizing chromatin landscape from aggregate and single-cell genomic assays using flexible duration modeling.
54	Lili Blumenberg, Vladislav Sviderskiy, Richard Possemato and Kelly Ruggles	Data-driven discovery of phosphorylation modules in cancer
55	Wojciech Rosikiewicz, Xiaowen Chen, Pilar M. Dominguez, Ari Melnick and Sheng Li	TET2 Deficiency Reprograms the Germinal Center B-cell Epigenome and Silences Genes Linked to Lymphomagenesis
56	Shu Wang, Manimozhi Manivannan, Saurabh Gulati, Sombeet Sahu, Dong Kim, Nianzhen Li and Nigel Beard	Using Machine Learning to Optimize Assays for Single-Cell Targeted DNA Sequencing
57	Yue Qiu, Tianhuan Lu, Hansaim Lim and Lei Xie	A Bayesian approach to accurate and robust signature detection on LINCS L1000 data
58	Saurabh V Laddha, Edaise M M da Silva, Kenneth Robzyk, Brian R Untch, Hua Ke, Natasha Rekhtman, John T Poirier, William D Travis, Laura H Tang and Chang S Chan	Integrative Genomic Characterization Identifies Molecular Subtypes of Lung Carcinoids
59	Luis Santos, Sydney Hart, Prashant Rabhhandari	Single Nuclei Adipocyte RNA sequencing (SNAP-Seq) Reveals Immune Cell-Adipocyte Crosstalk

DREAM Schedule
Monday - Day 1 – November 4, 2019
Go directly to: Tuesday, Nov 5 - Wednesday, Nov 6
START TIME	END TIME	SESSION TYPE
REGISTRATION 8:00 am - 6:00 pm Location: RRL Lobby
All DREAM Day talks to occur in the RRL Auditorium
8:40 am	9:00 am	Welcome and Introductory Remarks - Pablo Meyer
9:00 am	9:40 am	Keynote - Christopher Mason
Challenge Updates
9:40 am	9:50 am	Gustavo Stolovitzky & Justin Guinney Dream Future
9:50 am	10:05 am	Justin Guinney Update on Challenges: Tumor Deconvolution and Electronic Healthcare Record DREAM Challenges
10:05 am	10:15 am	Jim Costello DREAM Rheumatoid Arthritis Challenge 2: Automated Scoring of Radiographic Joint Damage
10:15 am	10:30 am	Julio Saez Rodriguez Single Cell Proteomics DREAM Challenge
10:30 am	10:40 am	Pablo Meyer Allen Institute Cell Lineage Reconstruction DREAM Challenge
10:40 am	11:00 am	Coffee Break with Posters
Challenge 1 - Preterm Birth Prediction: Transcriptomics DREAM Challenge Chair: Jim Costello
11:00 am	11:30 am	Adi Tarca Preterm Birth Prediction: Transcriptomics Challenge Overview Talk
11:30 am	11:50 pm	Pataki Balint Armin Best Performer Talk I: Blood test with machine learning to estimate the age of a pregnancy
11:50 pm	12:10 pm	Ziyan Wang Best Performer Talk II: Improving the Prediction of gestational age by using kernel-based approaches to denoise the data
12:10 pm	2:10 pm	Lunch on Own
Challenge 2 - IDG-DREAM Drug-Kinase Binding Prediction Challenge Chair: Julio Saez Rodriguez
2:10 pm	2:40 pm	Robert Allaway IDG-DREAM Drug-Kinase Binding Prediction Challenge Overview Talk
2:40 pm	3:00 pm	Team QED: Fangping Wan Best Performer Talk I: An ensemble learning based approach for the IDG-DREAM Drug-Kinase Binding Prediction Challenge
3:00 pm	3:20 pm	Team DMIS-DK: Sungjoon Park Best Performer Talk II: In Silico Molecular Binding Affinity Prediction with Multi-Task Graph Neural Networks
3:20 pm	3:40 pm	Team Aiwinteriscoming: Olexandr Isayev Best Performer Talk III: IDG-DREAM Drug-Kinase Binding Prediction Challenge: Subchallenge 2 winner team “AI Winter is Coming” solution
3:40 pm	4:20 pm	Coffee Break with Posters
4:20 pm	5:00 pm	Keynote - Chris Wiggins
Challenge 3 - Malaria DREAM Challenge Chair: Pablo Meyer
5:00 pm	5:30 pm	Geoffrey Siwo Malaria Challenge Overview Talk
5:30 pm	5:50 pm	Slim Fourati Best Performer Talk I: Predict the Artemisinin IC50 of malaria isolates using gene co-expression network analysis
5:50 pm	6:10 pm	Yoon Sanghoo Best Performer Talk II: Prediction of the Artemisinin IC50 of Malaria Isolate using in Vitro the Transcirptomics Data
6:10 pm	6:30 pm	Jiantao Guo Best Performer Talk III: Predict the resistance status of malaria isolates
6:30 pm	8:00 pm	DREAM Reception and Posters Location: Rooms 104

RSG Schedule
Tuesday – Day 2 – November 5, 2019
Go directly to: Monday, Nov 4 (DREAM) – Wednesday, Nov 6
START TIME	END TIME	SESSION TYPE
REGISTRATION 8:00 am - 5:00 pm Location: RRL Lobby
All RSG Day talks to occur in RRL Auditorium
9:00 am	9:15 am	Welcome
Special Session on Cancer Systems Biology Chair: Christina Leslie
9:15 am	10:00 am	Keynote - Sohrab Shah
10:00 am	10:15 am	Gurnit Atwal A deep learning system can accurately classify primary and metastatic cancers based on patterns of passenger mutations
10:15 am	10:30 am	Chloe B. Steen Landscape of Tumor Cell States and Cellular Ecosystems in Lymphoma
10:30 am	11:00 am	Coffee Break with Posters Location: RRL Lobby
Session 1 Chair: Christina Leslie
11:00 am	11:30 pm	New Investigator Spotlight Speaker - Elham Azizi
11:30 pm	11:45 pm	Anchal Sharma A computational genomic approach identifies that non-genetic heterogeneity is a major driver of phenotypic heterogeneity and evolutionary dynamics in non-small cell lung cancer
11:45 pm	12:00 pm	Hamed Najafabadi Domain-resolution maps of in vivo DNA binding reveal the molecular phenotypes associated with somatic mutations in zinc finger transcription factors
12:00 pm	12:15 pm	Bogdan Luca Atlas of clinically-distinct cell states and cellular ecosystems across human solid tumors
12:15 pm	1:00 pm	Keynote - Anshul Kundaje
12:45 pm	2:30 pm	Lunch on Own
Session 2 Chair: Sushmita Roy
2:30 pm	2:45 pm	Yuning Zhang Competition for DNA binding between paralogous transcription factors determines their genomic occupancy and regulatory functions
2:45 pm	3:00 pm	Yiming Kang TF binding locations and TF perturbation responses: The search for convergent evidence
3:00 pm	3:15 pm	Shaun Mahony Characterizing the sequence and chromatin predeterminants of induced transcription factor binding with bimodal neural networks
3:15 pm	3:30 pm	Eva Prakash Suggested best practices for interpreting deep learning models of regulatory DNA
3:30 pm	4:00 pm	Coffee Break with Posters Location: RRL Lobby
Session 3 Chair: Anthony Gitter
4:00 pm	4:15 pm	Yuri Pritykin A unified chromatin state and single-cell gene expression analysis defines a common differentiation trajectory towards T cell exhaustion
4:15 pm	4:30 pm	Chenyang Dong INFIMA Leverages Multi-Omic Model Organism Data to Identify Target Genes for Human GWAS Variants
4:30 pm	4:45 pm	Sneha Mitra RoboCOP: Multivariate state space model integrating epigenomic accessibility data to elucidate genome-wide chromatin occupancy
4:45 pm	5:30 pm	Keynote - Rich Bonneau Structure-Based Function Prediction using Graph Convolutional Networks
5:30 pm	7:00 pm	Reception with Poster viewing Location: Rooms 104 & 116
- top -
Wednesday – Day 3 – November 6, 2019
Go directly to: Monday, Nov 4 (DREAM) – Tuesday, Nov 5
START TIME	END TIME	SESSION TYPE
REGISTRATION 8:00 am - 5:00 pm Location: RRL Lobby
All RSG Day talks to occur in RRL Auditorium
9:00 am	9:15 am	Welcome
Session 4 Chair: Shaun Mahony
9:15 am	10:00 am	Keynote - Elodie Ghedin
10:00 am	10:15 am	Anthony Findley Context-specific genetic regulation of gene expression across cell types and treatments
10:15 am	10:30 am	Ralf Herwig Network integration and modelling of dynamic drug responses at multi-omics levels
10:30 am	10:45 am	George Rosenberger Inference of functional protein attributes from protein correlation profiles for the multi-omic elucidation of molecular mechanisms
10:45 am	11:15 am	Coffee Break with Posters Location: RRL Lobby
Session 5 Chair: Rich Bonneau
11:15 am	11:30 am	Shiqi Xie Global analysis of enhancer targets reveals convergent enhancer-driven regulatory modules
11:30 am	11:45 am	Hatice Osmanbeyoglu Integrative computational framework for linking signaling and transcriptional programs in single cells
11:45 am	12:00 pm	Nelson Johansen Combining deep single cell atlases and case-control bulk RNA studies to identify cell type-specific signatures of disease using deep learning
12:00 pm	12:45 pm	Keynote - Joakim Lundeberg Exploring data driven analysis of spatially resolved transcriptomes in situ and in single cells
12:45 pm	2:00 pm	Lunch on Own
Session 6 Chair: jian Ma
2:00 pm	2:45 pm	Keynote - Peng Yin
2:45 pm	3:00 pm	Anders Rasmussen CRISPR-decryptr: A Bayesian Pipeline for the Analysis of CRISPR Screens
3:00 pm	3:15 pm	Cynthia Kalita A powerful method to estimate cell-type specific QTLs from bulk expression by leveraging allelic imbalance
3:15 pm	4:00 pm	Coffee Break with Posters Location: RRL Lobby
Session 7 Chair: Itai Yanai
4:00 pm	4:15 pm	Xi Chen Tissue-specific enhancer functional networks for associating distal regulatory regions to disease
4:15 pm	4:30 pm	Austin Wang Allele-Specific QTL Fine-Mapping with PLASMA
4:30 pm	4:45 pm	Brittany Baur Leveraging Public Epigenomic Datasets to Examine the Role of Regulatory Variation in the Three-dimensional Organization of the Genome
4:45 pm	5:30 pm	Keynote - Alexis Battle
5:30 pm	7:00 pm	Reception with poster viewing Location: Room 104 & 116

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