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Informatics and Data Analytics Core (NS090408)

Specific Aims and Tasks

To expand and broaden the sharing and utilization of research resources and data across centers in order to accelerate the understanding of biological mechanisms for SUDEP, and to develop intervention and prevention measures to reduce SUDEP mortality. The main goal of this Informatics and Data Analytics U01 Core (IDAC) is to build on the progress already achieved through MEDCIS infrastructure and to expand and broaden the sharing and utilization of research resources among our partners. With access to biospecimen materials and alliances with stakeholder organizations, we continuously boost materials and data collection.

IDAC promotes and facilitates SUDEP research by expanding an integrated clinical and translation data resource for epilepsy; provides coordinated services and support for our members; empowering each investigator with web-based cohort search interface for data mining and hypothesis generation; data analytics and statistical support for in-depth analyses of multi-modal data collected in the shared and expanding CSR Data Repository.

Principal Investigators

  • GQ Zhang

    Dr. Zhang is Professor and Division Chief of Biomedical Informatics in the College of Medicine, University of Kentucky. He directs the new Institute of Biomedical Informatics (IBI) to catalyze informatics research and service on campus. He is the director and PI for CSR Informatics and Data Analytics Core (IDAC). Dr. Zhang has served as the PI/Multi-PI for the NCRR funded PhysioMIMI project (Multi- Modality, Multi-Resource Environment for Physiological and Clinical Research; NCRR-94681DBS78), NSRR National Sleep Research Resource project (R24HL114473), and Director of the Informatics Core for the PRISM project (P20NS076965) the precursor for IDAC. Dr. Zhang has over 10 years of experiences in large-scale, multi-center data integration, biomedical ontology development, query interface design and information retrieval, and agile, interface-driven access-control- grounded software development. He effectively brings cutting-edge computer science and informatics methodology to address biomedical data challenges such as those facing CSR. As the Principal Investigator of IDAC and Chief CSR Informatics Architect, Dr. Zhang provides oversight on all technical and resource aspects of the IDAC core and lead the operation of CSR resources and provide consultation for CSR scientific projects. Dr. Zhang serves in the CSR Steering Committee (SC) to coordinate CWW activities related the IDAC.

Core Personnel

Catherine P Jayapandian, PhD

Dr. Jayapandian is a Research Associate in the Medical Informatics Core in the Center for Clinical Investigation, CWRU. Her research interests  include High Performance Computing on Hadoop, Agile Web Development with Ruby on Rails, Semantic Web - Provenance Metadata Management, Knowledge Representation and Medical Image Processing and Visualization

Kenneth A Loparo, PhD

Dr. Loparo is the Nord Professor and Chair Department of Electrical Engineering and Computer Science, CWRU. His research interests include stability and control of nonlinear and stochastic systems with applications to large-scale electricity systems including generation and transmission and distribution; nonlinear filtering with applications to monitoring, fault detection, diagnosis, prognosis and reconfigurable control; information theory aspects of stochastic and quantized systems with applications to adaptive and dual control and the design of distributed autonomous control systems; the development of advanced signal processing and data analytics for monitoring and tracking of physiological behavior in health and disease.

Licong Cui, PhD

Licong Cui is an Assistant Professor in the Department of Computer Science at the University of Kentucky. Licong's research interests is in information retrieval, information extraction, text mining, knowledge representation and reasoning, knowledge discovery, ontology quality assurance, data integration and management, and big data analytics. In particular, her research goal is to develop computational methods and tools to solve real-world biomedical and health informatics problems. More details can be found at her webpage.

Shiqiang Tao, MS

Dr. Tao is Research Assistant Professor in the Division of Biomedical Informatics in the University of Kentucky.

Protocols and Manuals

Publication Links

  • Zhang GQ, Siegler T, Saxman P, Sandberg N, Mueller R, Johnson N, Hunscher D, Arabandi S (2010). VISAGE: A Query Interface for Clinical Research. PMID 21347154.
  • Zhang GQ and Bodenreider O (2010). Large-scale, Exhaustive Lattice-based Structural Auditing of SNOMED CT. AMIA Annual Symposium Proc 2010, pp. 922-926, (Distinguished Paper Award). PMID 21347113.
  • Sahoo S, Ogbuji C,, Luo L, Dong X, Cui L, Redline S, Zhang GQ (2011). MiDas: Automatic Extraction of a Common Domain of Discourse in Sleep Medicine for Multi-center Data Integration. PMID 22195180.
  • Tran V, Johnson N, Redline S, Zhang GQ (2011). OnWARD: Ontology-driven Web-based Framework for Multi-center Studies. PMID 21924379.
  • Sahoo S, Zhao M, Luo L, Bozorgi A, Gupta D, Lhatoo S, Zhang GQ (2012). OPIC: Ontology-driven Patient Information Capturing System for Epilepsy. AMIA Ann. Symposium Proc 2012. PMID 23304354.
  • Zhang GQ, Sahoo S, Lhatoo S (2012). From Classification to Epilepsy Ontology and Informatics. PMID 23647220.
  • Cui L, Bozorgi A, Lhatoo S, Zhang GQ, Sahoo S (2012). EpiDEA: Extracting Structured Epilepsy and Seizure Information from Patient Discharge Summaries for Cohort Identification. PMID 23647220.
  • Sahoo SS, Lhatoo SD, Gupta DK, Cui L, Zhao M, Jayapadian C, Bozorgi A, Zhang GQ (2013). Epilepsy and Seizure Ontology: Towards an Epilepsy Informatics Infrastructure for Clinical Research and Patient Care. PMID 23686934.
  • Sahoo SS, Zhang GQ, Lhatoo SD (2013). Epilepsy Informatics and an Ontology-driven Infrastructure for Large Database Research and Patient Care in Epilepsy. PMID 23647220.
  • Jayapandian CP, Chen CH, Bozorgi A, Lhatoo SD, Zhang GQ, Sahoo SS (2013). Electrophysiological Signal Analysis and Visualization using Cloudwave for Epilepsy Clinical Research. PMID 23920671.
  • Sahoo SS, Jayapandian CP, Chen CH, Bozorgi A, Lhatoo SD, Zhang GQ (2013). Heartbeats in the Cloud: Distributed Analysis of Electrophysiological “Big Data” using Cloud Computing for Epilepsy Clinical Research. PMID 24326538.