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21 * Sun, 8/7/2022, 2:00 PM - 3:50 PM CC-203AB
Advances of Statistical Methodologies in Proteogenomic Research — Topic Contributed Papers
Biometrics Section, Section on Statistics in Genomics and Genetics, International Indian Statistical Association
Organizer(s): Shrabanti Chowdhury, Icahn school of Medicine at Mount Sinai
Chair(s): Pei Wang, Icahn school of Medicine at Mount Sinai
2:05 PM Multilevel Modeling Accounts for Diverse Sources of Variation in Proteomic Experiments with Complex Designs
Olga Vitek, Northeastern University
2:25 PM DAGBagM: Learning Directed Acyclic Graphs of Mixed Variables with an Application to Identify Protein Biomarkers for Treatment Response in Ovarian Cancer
Shrabanti Chowdhury, Icahn school of Medicine at Mount Sinai; Ru Wang, University of California Davis; Jie Peng, University of California Davis; Pei Wang, Icahn school of Medicine at Mount Sinai
2:45 PM BayesDeBulk: A Flexible Bayesian Algorithm for the Deconvolution of Bulk Tumor Data
Francesca Petralia, Icahn School of Medicine at Mount Sinai
3:05 PM HID Machine: A Random Forest-Based High Order Interaction Discovery Method for High-Dimensional Genomic Data
Min Lu, University of miami; Yifan Sha, University of Miami; Xi Steven Chen, University of miami
3:25 PM Modeling Genomic and Proteomic Signals for the Early Detection of Cancer
Steven James Skates, Massachusetts General Hospital; Yiling Liu, Massachusetts General Hospital; Wenqing Jiang, Boston University School of Public Health; Bethan Powell, Kaiser-Permanente Northern California; Scott Lenttz, Kaiser-Permanente Southern California
3:45 PM Floor Discussion