Data Science to Data Sense Symposium

Biostatistics Program


Integrating Data Science and Statistics for Medical Advancement

Sponsored by Fred Hutch and University of Washington Cancer Consortium

 May 27, 2015

Pelton Auditorium, Fred Hutch Campus

CURRENT AGENDA (subject to change)

8:30   Welcome

          Gary Gilliland (Fred Hutch)

  Personalized Medicine and Data Science

8:50   Session 1: Vison: Promise of Data Science and what it will take to turn it into Data Sense

Suchi Saria (Johns Hopkins University)

            A $3 Trillion Challenge to Computational Scientists: Transforming Healthcare Delivery

Sean Mooney (University of Washington)

  Human Genome Interpretation using Biomedical Informatics: Opportunities and Challenges

9:55   Break

10:15  Session 2: Methods

Trevor Hastie (Stanford University)

            Statistical Learning – the Big Ideas in Principle and in Practice

Emily Fox (University of Washington)

            Scaling up to Meet the Demands of Big Data: Challenges and Solutions

11:20  Panel: Getting Closer to the Data

Susan Shortreed - GHC (EMR’s), Emilio Zagheni – UW (social network data), Emily Silgard – Fred Hutch (unstructured data and NLP), Sean Mooney - UW (genomics data)

12:30  Lunch

1:45   Session 3: Case Studies

Nigam Shah (Stanford University)

 Learning Practice-based Evidence from Electronic Medical Records

Daniela Witten (University of Washington)

            Estimating the Relative Pathogenicity of Human Genetic Variants

Mark Craven (University of Wisconsin)

            Inferring Host Gene Subnetworks Involved in Viral Replication

Joseph Sirosh (Microsoft Corporation Machine Learning and Information Management)

  Scalable Genomic Analyses with Cloud Based Big Data Platforms 

3:50   Break

4:10-4:55   Session 4: Education

Bill Howe (University of Washington eScience Institute)

Trevor Hastie (Stanford University)

Ali Shojaie (University of Washington)

4:55    Closing Remarks

5:00   Reception