Apr 06, 2011
from 03:30 PM to 04:30 PM
|Where||Brinkhous-Bullitt Building, Room 219|
|Contact Name||Lori Smith|
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Development of biomarkers that predict response to treatment and models that can direct development of new therapies requires integration of many complementary types of biomedical information captured at multiple scales. In the context of our caBIG® In Silico Brain Tumor Research Center, we are developing methodologies, information models, tools, and analytic pipelines that will make it feasible to systematically carry out large-scale integrative analyses of: 1) whole slide digital pathology and radiology based features, and 2) deep-sequencing data and patterns of protein and gene expression. The methods and tools will be designed to carry out the following closely interrelated tasks: 1) systematically manage, query and analyze results produced by data analyses composed of large numbers of interrelated algorithms, 2) compare results produced by workflows consisting of cascades of multiple algorithms, 3) efficiently manage result datasets that in aggregate will contain trillions of imaging derived features, 4) engage human neuropathologists and radiologists in validation of results and motivation of new analyses, and 5) support histological feature query and analysis patterns needed to link histological features with “omic” and outcome data.
Dr. Joel Saltz is Director of the Center for Comprehensive Informatics, Professor of Pathology, Biostatistics and Bioinformatics, Mathematics and Computer Science at Emory University, Adjunct Professor at Georgia Institute of Technology in the School of Computer Science and the Division of Computational Science, Georgia Research Alliance Eminent Scholar, and Georgia Cancer Coalition Distinguished Cancer Scholar. Prior to joining Emory, Dr. Saltz was Professor and Chair of the Department of Biomedical Informatics at The Ohio State University (OSU) and Davis Endowed Chair of Cancer at OSU. He served on the faculty of Johns Hopkins Medical School, University of Maryland College Park and Yale University in departments of Pathology and Computer Science. He received his MD and PhD (computer science) degrees at Duke University and is a board certified Clinical Pathologist trained at Johns Hopkins University. Dr. Saltz’s principal research objective is to develop principles, techniques and tools that can be used by biomedical researchers to assemble a coherent biomedical picture by integrating information from multiple, complementary data sources. Over the past 25 years he has led projects to develop innovative techniques, methodologies, algorithms and software systems to support data federation, high-performance computing, data management, and data analyses. He has played multiple leadership roles in the NCI-funded cancer Biomedical Informatics Grid (caBIG®) program since the program's inception, and led the academic group responsible for design and development of the current caGrid infrastructure.