Michael Marron, Ph.D., Director Division of Biomedical Technology National Center for Research Resources National Institutes of Health Department of Health and Human Services Bethesda, Maryland, USA Biomedical Informatics Research Network

January Biomedical Informatics Research Network Testbed for biomedical knowledge infrastructure

3 BIRN Biomedical Informatics Research Network A testbed for a biomedical knowledge infrastructure Federated database of neuroimaging data Fusion of diverse data sources (location; level of aggregation) Grid access to computational resources Datamining software Scalable and extensible Driven by research needs-pull, not technology-push

BIRN Sites

BIRN Information Integration protein localization What is the cerebellar distribution of rat proteins with more than 70% homology with human NCS-1? Integrated View Mediator morphometryneurotransmission Web CaBP, Expasy Wrapper Integrated View Definition

January BIRN Grid Infrastructure The BIRN Portal is built on many “layers” Layers are modular, allowing for extension of any layer without great disruption to the entire system Every Layer has its own complexity and administration that was previously passed on to the end-user Portal centralizes all adminis- trative details of each layer into a single username and pass phrase

BIRN Grid Infrastructure BIRN Toolkit Viewing/Visualization Queries/ResultsApplications Data Management Computation MCAT Data Storage Grid Middleware Collaboration Globus Distributed Resources Mediator Database GridPort Toolkit SRB BIRN Portal Custom APIs Mediator APIVisualization APIs Security API

January BIRN Knowledge Integration BIRN Knowledge Integration Supports queries across heterogeneous data sources Query Mediator Layer Wrapper Layer Mediator Services API Query interfaceResult interface Query Formulation Source Model Lifting Source Registration Deductive Engine Query Processing HTML Files XML RDB OODB Model Reasoner Optimizer SRB

January Mouse BIRN Studying animal models of disease across dimensional scales to test hypothesis with human neurological disorders  Experimental Allergic Encephalomyelitis (EAE) mouse models (both chemically induced and transgenic) exhibit episodic weakness and demyelination characteristic of multiple sclerosis  Dopamine Transporter (DAT) knockout mouse for studies of schizophrenia, attention-deficit hyperactivity disorder (ADHD), Tourette’s disorder and substance abuse  Using an alpha-synuclein mouse to model the symptoms/pathology of Parkinson’s Disease Duke, UCLA, UC San Diego, Cal Tech

January Mouse BIRN Duke - CIVM UCSD-NCMIR & Duke - CIVN UCSD-NCMIR Reconstructed spiny dendrite Integrating brain data across scales and disciplines Coronal sections of mouse brains

January Morphology BIRN Examining neuroanatomical correlates of neuropsychiatric illnesses, including Unipolar Depression, mild Alzheimer’s Disease and mild cognitive impairment Combining data from multiple acquisition sites Increase statistical power for study of rare populations Harvard (MGH and BWH), Duke, UCLA, UC– San Diego, Johns Hopkins

Morphology BIRN Model based three dimensional medical image segmentation Harvard-BWH 3D-Slicer - An Integrated visualization system for surgical planning and guidance using image fusion and interventional imaging Dynamics of gray matter loss rates, mapped in a schizophrenia population UCLA-LONI Harvard-MGH Surface based coordinate system Harvard-BWH

January Functional BIRN  Developing a common fMRI protocol to study regional brain dysfunction related to the progression and treatment of schizophrenia  Investigating techniques to insure interoperability of existing tools for multi-modal analysis  Correlating functional data with anatomical data acquired from the Morphology test-bed to study if there are neuroanatomical correlates with cognitive dysfunction across disorders  UCLA, UC San Diego, UC Irvine, Harvard (MGH and BWH), Stanford, Minnesota, Iowa, New Mexico, Duke/U. North Carolina

January Functional BIRN Stanford – Lucas Center fMRI response at 3T and 1.5T with identical software and hardware platforms Patients with schizophrenia show abnormal modulation of temporal and frontal regions during semantic processing Harvard-MGH neocortical network mediates semantic processing of sentences in healthy individuals

January BIRN Coordinating Center  Deploy a network infrastructure capable of quickly moving large amounts of data between BIRN sites across the country  Create federated databases pertaining to the BIRN scientific test-beds  Develop software to find, compare, and analyze complex neurological imaging data  Ensure regulatory compliance (HIPAA) without inhibiting collaboration  UC San Diego

January BIRN NOC Monitoring 24x7 Operations Monitoring Gigabit Network Probes Internet 2 GB Switches UCSD/SDSC Network BIRN Network Management BIRN Site Rack BIRN Network Operations Center Standardized Site Rack N2400 NAS TB Cisco 4006 DL380 Grid POP DL380 - Network Stats GigE Net Probe APC UPS DL380 Network Switch BIRN Statistics BIRN Network Probe Network Attached Storage Grid POP/SRB, Globus General purpose ( eg., encryption) UPS for Rack NCRR Ultimately, access from anywhere to BIRN data everywhere Wired and Wireless NOC Servers and Testers/Analyzers

January BIRN CC Services  Network Monitoring  Statistics & Measurement  7 x 24 Help Desk  Problem Tracking  High Level Project Management  Portal Services & Tools Integration  Training  Data Integration  Visualization Tools  Documentation – web site, best practices, lessons learned, checklists

January Challenges Large data sets  ISCAR - information storage, curation, archiving, and retrieval  Bandwidth issues  Quality control of data only analyzed by machine  Visual interfaces for complex data sets Fostering collaboration  Reward structures in government and academic institutions  Intellectual property issues  Data integrity  Resistance to collaborate with competitors Data sharing issues (ownership, privacy, authorship)

January More Challenges Federated DB /Knowledge Engineering  Dictionaries & Ontologies  Integrating different data types  Accessing legacy systems  Distributed query computations High-level management of projects  Overcome technical & institutional barriers  Degree of centralization needed  Role of standards  Project subdivision and optimization

January BIRN Future  Addition of new sites in a rapid, well-defined, affordable fashion  Grid-based National Clinical Research Network  Cross-species integration of data  Characterization of treatment at multiple levels  Expand model to other areas of biomedical research