Biomedical Informatics Infrastructure

Active Projects

Informatics for Integrative Brain Tumor Whole Slide Analysis - funded by the National Library of Medicine, this project develops, deploys, and evaluates methodologies, information models, tools, and analytic pipelines that will make it feasible to systematically carry out large-scale comparative analyses of brain tumor histological features using whole slide images and of patterns of protein and gene expression. The research and development effort involves (1) highly optimized algorithms and analytic pipelines which enable investigators to carry out large-scale comparative analyses of brain tumor histological features using whole slide images and of patterns of protein and gene expression, (2) flexible information models to manage information associated with analysis of brain tumor whole virtual slide data, (3) runtime systems that take advantage of high performance computing platforms to scale image analyses to large datasets. The methods and tools will be used to determine the relationship between image-based tumor signatures and clinical outcome, gene expression category, genetic gains/losses and methylation status and map the activity of signal transduction pathways and transcriptional networks relative to the tumor microenvironment using quantitative multiplex quantum dot immunohistochemistry and histology feature descriptions. This project is a collaborative effort between Stony Brook University (Joel Saltz, Tahsin Kurc), Emory University (Daniel Brat, Lee Cooper, David Gutman, Fusheng Wang, Jun Kong, Roberd Bostick, Carlos Moreno), and Rutgers Cancer Institute of New Jersey (David J. Foran).

Past Projects

CardioVascular Research Grid (CVRG)  -- funded by the National Heart, Lung, and Blood Institute as a resource to develop and disseminate informatics tools that address the needs of cardiovascular research studies and facilitate collaborative, multi-institutional projects. CVRG is lead by The Johns Hopkins University (Rai Winslow, overall PI) and is a collaboration between JHU, Emory University, Stony Brook University, Wake Forest University, and The University of Chicago. [project web site]

Analytic Information Warehouse and Eureka! -- funded in part by the National Institutes of Health through the CVRG, Atlanta Clinical and Translational Science Institute, and the Minority Health GRID projects, this project develops tools that enable healthcare institutions and researchers to use clinical databases to perform detailed discovery, characterization and comparison of patient cohorts. This is a joint project between Emory University (Andrew Post, Biomedical Informatics Department) and Stony Brook University (Joel Saltz and Tahsin Kurc, Biomedical Informatics Department). [project web site]

Related Publications

  • A. Post, T. Kurc, S. Cholleti, J. Gao, X. Lin, W. Bornstein, D. Cantrell, D. Levine, S. Hohmann, J. Saltz: The Analytic Information Warehouse (AIW): A platform for analytics using electronic health record data, Journal of Biomedical Informatics, 46(3), pp. 410-424, 2013. [paper]  
  • A. Post, T. Kurc, R. Willard, H. Rathod, M. Mansour, A. Pai, W. Torian, S.  Agravat, S. Sturm, J. Saltz, “Temporal Abstraction-based Clinical Phenotyping with Eureka!”, accepted for presentation and publication at the AMIA 2013 Annual Symposium, 2013.
  • J. Brown, M. Ahamad, M. Ahmed, D. Blough, T. Kurc, A. Post, and J. Saltz, "Redactable and Auditable Data Access for Bioinformatics Research," Proceedings of the AMIA Summit on Clinical Research Informatics, pp. 21-25, 2013. [paper]
  • Post A, Kurc T, Overcash M, Cantrell D, Morris T, Eckerson K, Tsui C, Willey T, Quyyumi A, Eapen D, Umpierrez G, Ziemer D, Saltz J. A Temporal Abstraction-based Extract, Transform and Load Process for Creating Registry Databases for Research. AMIA Joint Clinical Research Informatics and Translational Bioinformatics Summit; San Francisco,  2011. [paper]
  • Winslow, R. L., Saltz, J., Foster, I., Carr, J. J., Ge, Y., Miller, M. I, Younes, L., Geman, D., Graniote, S., Kurc, T., Madduri, R., Ratnanather, T., Larkin, J., Ardekani, S., Brown, T., Kolasny, A., Reynolds, K., Shipway, M., Toerper, M. (2011) The CardioVascular Research Grid (CVRG) Project, Proceedings of the AMIA Summit on Translational Bioinformatics, 2011, pgs. 77-81. [paper]
  • Post A, Kurc T, Butler J, Saltz J. Architecture of an Analytic Information Warehouse for Discovering Risk Factor Models of Disease in Quality Improvement and Research. American Medical Informatics Association (AMIA) Summit on Translational Bioinformatics. San Francisco, CA; 2010. 
  • M. Kim, J. Cobb, M.J. Harrold, T. Kurc, A. Orso, J. Saltz, A. Post, K. Malhotra and S. Navathe, "Efficient Regression Testing of Ontology-Driven Systems", Proceedings of the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2012). [paper]
  • A. Mohan, D. Blough, T. Kurc, A. Post, and J. Saltz, "Detection of Conflicts and Inconsistencies in Taxonomy-based Authorization Policies," Proceedings of the 2011 IEEE International Conference on Bioinformatics & Biomedicine, pp. 590-594, 2011. [paper]
  • Kim M, Kurc T, Orso A, Cobb J, Gutman D, Harrold M, Sharma A, Post A, Saltz J. An Informatics Framework for Testing Data Integrity and Correctness of Federated Biomedical Databases. AMIA Joint Clinical Research Informatics and Translational Bioinformatics Summit; San Francisco.  2011. [paper]
  • T. Kurc, S. Hastings, V.S. Kumar, S. Langella, A. Sharma, T. Pan, S. Oster, D. Ervin, J. Permar, S. Narayanan, Y. Gil, E. Deelman, M. Hall and J. Saltz: HPC and Grid Computing for Integrative Biomedical Research. International Journal of High Performance Computing Applications, Special Issue, the Workshop on Clusters and Computational Grids for Scientific Computing, Vol. 23(3), pp. 252-264, 2009. [paper]
  • S. Langella, S. Hastings, S. Oster, T. Pan, A. Sharma, J. Permar, D. Ervin, B. Cambazoglu, T. Kurc, and J. Saltz, ”Sharing Data and Analytical Resources Securely in a Biomedical Research Grid Environment”, Journal of American Medical Informatics Association, Vol. 15(3), pp. 363-373, 2008. [paper]
  • S. Oster, S. Langella, S. L. Hastings, D. W. Ervin, R. Madduri, J. Phillips, T. Kurc, F. Siebenlist,  P. A. Covitz, K. Shanbhag, I. Foster, J. H. Saltz, ”caGrid 1.0: An Enterprise Grid Infrastructure for Biomedical Research”, Journal of the American Medical Informatics Association (JAMIA), Vol. 15, pp. 138-149, 2008. [paper]
  • S. Langella, S. Oster, S. Hastings, F. Siebenlist, J. Phillips, D. Ervin, J. Permar, T. Kurc, J. Saltz, The Cancer Biomedical Informatics Grid (caBIG) Security Infrastructure, The American Medical Informatics Association (AMIA) Symposium, November 2007. [paper]
  • S. Oster, S. Langella, S. Hastings, E. David, R. Madduri, T. Kurc, F. Siebenlist, I. Foster, K. Shanbhag, P. Covitz, J. Saltz, caGrid 1.0: A Grid Enterprise Architecture for Cancer Research, The American Medical Informatics Association (AMIA) Symposium, November 2007. [paper]
  • G. Teodoro, T. Pan, T. Kurc, J. Kong, L. Cooper, and J. Saltz: Efficient Irregular Wavefront Propagation Algorithms on Hybrid CPU-GPU Machines, Parallel Computing, 39(4-5), 189-211, 2013. [paper]
  • J. Saltz, G. Teodoro, T. Pan, L. Cooper, J. Kong, S. Klasky, T. Kurc: Feature-based analysis of large-scale spatio-temporal sensor data on hybrid architectures, International Journal of High Performance Computing Applications, 27(3), pp. 263-272, 2013. [paper]
  • F. Wang, J. Kong, J. Gao, L. Cooper, T. Kurc, Z. Zhou, D. Adler, C. Vergara-Niedermayr, B. Katigbak, D. Brat, J. Saltz:  A high-performance spatial database based approach for pathology imaging algorithm evaluation, Journal of pathology informatics, 4, 2013. [paper]
  • F. Wang, J. Kong, L. Cooper, T. Pan, T. Kurc, W. Chen, A. Sharma, C. Niedermayr, T.W. Oh, D. Brat, A.B. Farris, D.J. Foran, J. Saltz: A data model and database for high-resolution pathology analytical image informatics. J Pathol Inform 2 (2011) 32. [paper]
  • D Foran, L Yang, W Chen, J Hu, L Goodell, M Reiss, F Wang, T Kurc, T Pan, A Sharma, J Saltz. ImageMiner: A Software System for Comparative Analysis of Tissue Microarrays Using Content-Based Image Retrieval, High-Performance Computing, and Grid Technology. Journal of the American Medical Informatics Association. May 23, 2011. 18:352-353. PMID: 21606133. [paper]
  • V.S. Kumar, T. Kurc, V. Ratnakar, J. Kim, G. Mehta, K. Vahi, Y.L. Nelson, P. Sadayappan, E. Deelman, Y. Gil, M. Hall and J. Saltz: Parameterized Specification, Configuration and Execution of Data-Intensive Scientific Workflows. Cluster Computing: the Journal of Networks, Software Tools and Applications, Special Issue on High Performance Distributed Computing, Vol. 13(3), pp. 315-333, 2010. [paper]
  • T. Kurc, S. Hastings, V.S. Kumar, S. Langella, A. Sharma, T. Pan, S. Oster, D. Ervin, J. Permar, S. Narayanan, Y. Gil, E. Deelman, M. Hall and J. Saltz: HPC and Grid Computing for Integrative Biomedical Research. International Journal of High Performance Computing Applications, Special Issue, the Workshop on Clusters and Computational Grids for Scientific Computing, Vol. 23(3), pp. 252-264, 2009. [paper]
  • N. Vydyanathan, S. Krishnamoorthy, G.M. Sabin, U.V. Catalyurek, T. Kurc, P. Sadayappan, J. Saltz: An Integrated Approach to Locality-Conscious Processor Allocation and Scheduling of Mixed-Parallel Applications. IEEE Trans. Parallel Distrib. Syst., Vol. 20(8), pp. 1158-1172, 2009. [paper]
  • V. S. Kumar, S. Narayanan, T. Kurc, J. Kong, M. N. Gurcan, J. H. Saltz, ”Analysis and Semantic Querying in Large Biomedical Image Datasets”, IEEE Computer Magazine, special issue on Data-Intensive Computing, Vol. 41(4), pp. 52-59, 2008. [paper]
  • V. S. Kumar, B. Rutt, T. Kurc, U. V. Catalyurek, T. C. Pan, S. Chow, S. Lamont, M. Martone, J. H. Saltz, ”Large-scale Biomedical Image Analysis in Grid Environments”, IEEE Transactions on Information Technology in Biomedicine, Vol. 12(2), pp. 154-161, 2008. [paper]
  • G. Teodoro, T. Tavares, R. Ferreira, T. Kurc, W. Meira Jr., D. O. Guedes, T. Pan, J. H. Saltz, ”A Run-time System for Efficient Execution of Scientific Workflows on Distributed Environments”, International Journal of Parallel Programming, Vol. 36(2), pp. 250-266, 2008. [paper]
  • G. Teodoro, T. Pan, T. Kurc, J. Kong, L. A. Cooper, N. Podhorszki, S. Klasky, J. Saltz, "High-throughput Analysis of Large Microscopy Image Datasets on CPU-GPU Cluster Platforms," in the 27th IEEE International Parallel and Distributed Processing Symposium (IPDPS), Boston, Massachusetts, USA. May 20-24, 2013. [paper]
  • P. Widener, T. Kurc, W. Chen, F. Wang, L. Yang, J. Hu, V. Kumar, V. Chu, L. Cooper, J. Kong, A. Sharma, T. Pan, J. Saltz, and D. Foran: High Performance Computing Techniques for Scaling Image Analysis Workflows. Lecture Notes in Computer Science, Applied Parallel and Scientific Computing (PARA 10), Springer, p67-77, 2012. [paper]
  • G. Teodoro, T. Kurc, T. Pan, L. Cooper, J. Kong, P. Widener, and J. Saltz: Accelerating Large Scale Image Analyses on Parallel, CPU-GPU Equipped Systems. The 26th IEEE International Parallel and Distributed Processing Symposium (IPDPS), May 2012. [paper]
  • P. Widener, T. Kurc, W. Chen, F. Wang, L. Yang, J. Hu, V. Kumar, V. Chu, L. Cooper, J. Kong, A. Sharma, T. Pan, J. Saltz, D. Foran: Grid-Enabled, High-performance Microscopy Image Analysis. The 2nd International Workshop on High-Performance Medical Image Computing for Image-Assisted Clinical Intervention and Decision-Making (HP-MICCAI 2010) Beijing, China, September 2010.
  • F. Wang, T. Kurc, P. Widener, T. Pan, J. Kong, L. Cooper, D. Gutman, A. Sharma, S. Cholleti, V. Kumar and J. Saltz: High-performance Systems for In Silico Microscopy Imaging Studies. The 7th International Conference on Data Integration in the Life Sciences, Gothenburg, Sweden, August 2010. [paper]
  • V.S. Kumar, T. Kurc, G. Mehta, K. Vahi, V. Ratnakar, J. Kim, E. Deelman, Y. Gil, P. Sadayappan, M. Hall and J. Saltz, ”An Integrated Framework for Parameter-based Optimization of Scientific Workflows”, Proceedings of the ACM International Symposium on High Performance Distributed Computing (HPDC), June 2009. [paper]
  • V.S. Kumar, T. Kurc, J. Saltz, G. Abdulla, S. Kohn, and C. Matarazzo, Architectural Implications for Spatial Object Association Algorithms, the 23rd IEEE International Parallel and Distributed Processing Symposium (IPDPS 09), Rome, Italy, May, 2009. [paper]
  • S. Narayanan, U. Catalyurek, T. Kurc, and J. Saltz: Parallel Materialization of Large ABoxes. The 24th Annual ACM Symposium on Applied Computing (SAC 2009), Hawaii, USA, March, 2009. [paper]
  • G. Khanna, U. Catalyurek, T. Kurc, R. Kettimuthu, P. Sadayappan, I. Foster, and J. Saltz, ”Using Overlays For Efficient Data Transfer Over Shared Wide-Area Networks”, Proceedings of SC2008 High Performance Computing, Networking, and Storage Conference, Nov 2008. [paper]
  • G. Khanna, U. V. Catalyurek, T. Kurc, R. Kettimuthu, P. Sadayappan, J. H. Saltz, ”A Dynamic Scheduling Approach for Coordinated Wide-Area Data Transfers using GridFTP”, The 22nd IEEE International Parallel & Distributed Processing Symposium (IPDPS’08), April, 2008. [paper]
  • V. Kumar, T. Kurc, J. Kong, U. Catalyurek, M. Gurcan, J. Saltz, Performance vs. Accuracy Trade-offs for Large-scale Image Analysis Applications, Cluster 2007, 2007. [paper]