Statistical Data Integration Challenges in Computational Biology: Regulatory Networks and Personalized Medicine
Videos from BIRS Workshop
Chad Creighton, Baylor College of Medicine
Monday Aug 12, 2013 09:04 - 09:37
Pathway-level insights from The Cancer Genome Atlas (TCGA)
Yoav Gilad, University of Chicago
Monday Aug 12, 2013 09:40 - 10:15
Understanding gene regulation (or not)
Stephen Montgomery, Stanford University
Monday Aug 12, 2013 10:19 - 11:02
The extent and impact of rare non-coding variants in humans
David Haussler, University of California at Santa Cruz
Monday Aug 12, 2013 11:22 - 12:24
Large-scale comparative genomics for cancer research
Benjamin Haibe Kains, Institut de Recherches Cliniques de Montréal
Monday Aug 12, 2013 16:21 - 16:57
Prediction of Drug Response in Cell Lines: Are Pharmacogenomic Datasets Consistent?
Pei Wang, Fred Hutchinson Cancer Research Center
Tuesday Aug 13, 2013 09:08 - 09:44
Regularized multivariate regression approaches for integrative genomic analysis
Ronglai Shen, Memorial Sloan-Kettering Cancer Center
Tuesday Aug 13, 2013 09:44 - 10:20
Pattern discovery and cancer gene identification in integrated cancer genomic data
Hongyu Zhao, Yale University
Tuesday Aug 13, 2013 11:15 - 12:09
Joint analysis of expression profiles from multiple cancers to identify microRNA-gene interactions
Christina Kendziorski, UW-Madison
Tuesday Aug 13, 2013 13:32 - 14:08
Latent Dirichlet allocation models to enable personalized genomic medicine
Ingo Ruczinski, Johns Hopkins University
Tuesday Aug 13, 2013 14:27 - 14:45
Sequencing family members to detect disease risk variants
Venkatraman Seshan, Memorial Sloan Kettering Cancer Center
Tuesday Aug 13, 2013 14:46 - 15:16
To adjust or not to adjust: the design and analysis of an epidemiologic study
Manolis Kellis, Massachusetts Institute of Technology and Broad Institute
Tuesday Aug 13, 2013 16:37 - 17:20
Regulatory and systems genomics of complex traits and intermediate molecular phenotypes
Pierre Neuvial, CNRS & University of Evry
Wednesday Aug 14, 2013 09:10 - 09:47
Improved performance evaluation of DNA copy number analysis methods in cancer studies
Laurent Jacob, Centre national de la recherche scientifique
Wednesday Aug 14, 2013 09:47 - 10:24
Correcting gene expression data when neither the unwanted variation nor the factor of interest are observed
Roger Peng, Johns Hopkins University
Wednesday Aug 14, 2013 10:24 - 11:02
Reproducible Research with Evidence-based Data Analysis
Keith Baggerly, MD Anderson Cancer Center
Wednesday Aug 14, 2013 11:21 - 12:22
When is Reproducibility an Ethical Issue? Genomics, Personalized Medicine, and Human Error
Kasper Hansen, John Hopkins University
Thursday Aug 15, 2013 09:06 - 09:42
A genome-wide look at DNA methylation
Wolfgang Huber, EMBL
Thursday Aug 15, 2013 09:42 - 10:17
Differential analysis of count data from high-throughput sequencing
Mark Segal, UCSF
Thursday Aug 15, 2013 10:18 - 10:48
Reproducibility of 3D chromatin configuration reconstructions
Jeffrey Leek, Johns Hopkins Bloomberg School of Public Health
Thursday Aug 15, 2013 11:10 - 11:59
Statistical processes for facilitating personalized medicine
Anshul Kundaje, Stanford University
Thursday Aug 15, 2013 13:53 - 14:29
Learning long-range regulatory interactions and unified gene regulation programs in diverse human cell-types
X. Shirley Liu, Dana-Farber Cancer Institute and Harvard University
Thursday Aug 15, 2013 15:20 - 16:15
Integrating sequencing and microarray data to identify novel functions of epigenetic regulators in cancer
David Stephens, McGill University
Friday Aug 16, 2013 08:40 - 09:16
Statistical modeling and computation for methylation profiles in the BLK gene region
Noah Simon, Stanford University
Friday Aug 16, 2013 09:16 - 09:41
Estimating Many Effect-sizes Bayesian Estimation as a Frequentist
Alexis Battle, Stanford University
Friday Aug 16, 2013 09:43 - 10:20
Characterizing the genetic basis of transcriptome diversity through RNA-sequencing
Davide Risso, Weill Cornell Medicine
Friday Aug 16, 2013 10:29 - 11:07
The role of spike-in standards in the normalization of RNA-Seq
