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RSG with DREAM 2019 | November 4-6, 2019 | New York, USA |Poster Presentations Schedule

Poster Presentations Schedule

DREAM Poster Session  - Monday, 6:30 pm - 8:00 pm
Location: Rooms 104

RSG Poster Session Odd Numbers - Tuesday, 5:30 pm - 7:00 pm
Location: Rooms 104 & 116

RSG Poster Session Even Numbers - Wednesday, 5:30 pm - 7:00 pm
Location: Rooms 104 & 116


  • If you are in the Odd Number Session, you may set up your poster any time between 8:30 am and Noon on Tuesday and must remove your poster by 8pm on Tuesday. All remaining posters will be discarded.
  • If you are in the Even Number Session, you may set up your poster any time between 8:30 am and Noon on Wednesday and must remove your poster by 8pm on Wednsday. All remaining posters will be discarded.

Poster Display Size:
When preparing accepted posters please note that your poster should not exceed the following dimensions: 46 inches wide by 45 inches high. There will be 2 posters per side on the each poster board.

As of October 8, 2019. Subject to change without notice.

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

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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
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)
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

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

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