AMIA TBI Advanced Program (TMO:TMKB Paper presentation March 8th San Francisco)

For those interested - the information on the advance program for the AMIA 2001 Summit on Translational BioInformatics has been published:

Here's the URL: http://jointsummits2011.amia.org/TBI/advance-program

HCLSIG has 2 presentations at AMIA, one on Chinese Medicine (lead by Matthias Samwald) and the other on Translational Medicine Knowledge Base, chaired by Michel Dumontier and before him, Susie Stephens.  Congratulations!

Joanne

10:30 am – 12:00 pm
 
TBI-10 Papers and Podium Abstracts
Developing a Semantic Framework for Clinical and Translational Research, Susan A. Matney, University of Utah
The Translational Medicine Ontology and Knowledge Base: Using Semantic Web Technology in Personalized Medicine for Data Integration, Joanne S. Luciano, Rensselaer Polytechnic Institute and Predictive Medicine Inc
Assessing the Complexity of Clinical Data Requests, Daniel Capurro, University of Washington and Universidad Católica de Chile
OnWARD: Ontology-driven Web-based Framework for Multi-center Clinical Studies, Van Anh Tran, Case Western Reserve University Cleveland, Ohio, USA

---> Poster session 5-6 PM (all days)

10:30 am – 12:00 pm	Scientific Sessions
TBI-09 Papers and Podium Abstracts

Using Clinical Trial Data to Identify Candidates for Drug Re-Purposing, Marco D. Sorani, Genentech, Inc

A Computational Analysis Pipeline for Determining Nut Allergy In Vitro, Noah Zimmerman, Stanford University

An Environment-wide Association Study (EWAS) on Serum Lipid Levels, Chirag J. Patel, Stanford University School of Medicine

Whole Exome Sequencing Study Incidentally Reveals Genetic Cause of one Case of Idiopathic Hemolytic Anemia, Reid Robison, University of Utah

TBI-10 Papers and Podium Abstracts

Developing a Semantic Framework for Clinical and Translational Research, Susan A. Matney, University of Utah

The Translational Medicine Ontology and Knowledge Base: Using Semantic Web Technology in Personalized Medicine for Data Integration, Joanne S. Luciano, Rensselaer Polytechnic Institute and Predictive Medicine Inc

Assessing the Complexity of Clinical Data Requests, Daniel Capurro, University of Washington and Universidad Católica de Chile

OnWARD: Ontology-driven Web-based Framework for Multi-center Clinical Studies, Van Anh Tran, Case Western Reserve University Cleveland, Ohio, USA

TBI-11 Papers and Podium Abstracts

Knowledge-based analysis implicates hypoxia in beta-blocker response, Hannah Tipney, University of Colorado Denver

Finding Cellular Response to Varying Doses of Cancer Therapeutics, Tiffany J. Chen, Stanford University

A novel signal detection algorithm to identify hidden drug-drug interactions in the FDA Adverse Event Reporting System, Nicholas P. Tatonetti, Stanford University

PAPAyA: Applications in Oncology Decision Support, Angel Janevski, Philips Research North America

TBI-12 Panel

Associating Semantic and Genomic Information

Lewis J. Frey, Karen Eilbeck, University of Utah, Robert Freimuth, Mayo Clinic, Michael Krauthammer, Yale University School of Medicine, Nigam Shah, Stanford University

This panel will examine methods and implications of associating semantic and genomic information. The focus will be on the following areas: (1) annotation of sequence data, (2) community collection and maintenance of semantic information, (3) reasoning over large data sets and (4) hypothesis generation from semantics data. With the growth of whole genome sequencing, there is an acute need to associate semantic information with genetic information, because by itself, a genomic sequence is only a string of letters. The addition of semantic knowledge to the genetic information is paramount. Coupling this information has already started to take place. How this semantic information is collected and maintained in a community informed and curated approach is important to the overall effort. To ensure quality of the semantic information, it needs to be validated by experts and tools are needed to support this effort. If implemented well, such work opens up the possibility of using the semantic technology to reason over multi-modal omics data. In addition to omics analysis, there is reasoning over the semantic information itself. Here, there are questions of how to generate and test hypotheses from such semantic information.