Cancer Panomics: Integrative Analysis of Cancer High-Throughput "Omics" Data to Enable Precision Oncology #panomics14 organized by Francisco De La Vega, Josh Stuart, Gunnar Rätsch, & Søren Brunak

8:50-9:05 An Integrated Approach To Blood-Based Cancer Diagnosis And Biomarker Discovery; Martin Renqiang Min, …, Rachel Ostroff

9:05-9:20 Multiplex Meta-Analysis of Medulloblastoma Expression Studies with External Controls; Alexander A. Morgan, …, Samuel H. Cheshier

9:20-9:35 Systematic Assessment of Analytical Methods for Drug Sensitivity Prediction from Cancer Cell Line Data; In Sock Jang, …, Adam A. Margolin

9:35-9:50 The Stream Algorithm and Applications to Pharmacogenomic Prediction of Cancer Cell Line Sensitivity; Elias Chaibub Neto, …, Adam A. Margolin

9:50-10:05 Integrative Analysis of Two Cell Lines Derived from a Non-Small-Lung Cancer Patient – A Panomics Approach; Oleg Mayba, …, Zemin Zhang

10:05-10:20 Detecting Statistical Interaction Between Somatic Mutational Events and Germline Variation from Next-Generation Sequence Data; Hao Hu, Chad D. Huff

10:20-10:35 Tumor Haplotype Assembly Algorithms for Cancer Genomics; Derek Aguiar, …, Sorin Istrail

10:35-10:45 Short break 10:45-11:00 Sharing Information to Reconstruct Patient-Specific Pathways in Heterogeneous

Diseases; Anthony Gitter, …, Ernest Fraenkel 11:00-11:15 Extracting Significant Sample-Specific Cancer Mutations Using Their Protein

Interactions; Liviu Badea 11:15-11:40 Talk+Discussion: Inferring genomic predictors of cancer phenotypes from high

throughput cancer genomics data; Adam Margolin 11:40-12:00 Talk+Discussion: Cancer comorbidities and disease trajectories from electronic

patient records and registry data; Søren Brunak