1、Lei Liu, Ph.D.,The Fifth China-US Roundtable on Scientific Data Cooperation October 27-28, 2011, Beijing, China,Biomedical Data Integration and Knowledgebase,Shanghai Center for Bioinformation Technology And Shanghai Institutes for Biological Sciences, CAS,Part 1: Ontology,Knowledge Management Data
2、Integration and Exchange Semantic Interoperability Decision Support and Reasoning,Knowledge Management,Annotating Data and Resources Accessing Biomedical Information Mapping across Biomedical Ontologies,Ontology,Data Exchange & Semantic Interoperability,Information and Data Integration Semantic Inte
3、roperability,Ontology,Decision Support and Reasoning,Data Selection Data Aggregation Decision Support Natural Language Processing Applications Knowledge Discovery,Ontology,Example: Ontology Server,Example: Building Knowledge Base,Edit,Example: Building Knowledge Base,Search tool,Part 2: SNOMED CT,Sy
4、stematized Nomenclature of MedicineReference Terminology(SNOMED RT),Clinical Terms(CT),SNOMED CT,CAP,NHS,CAP: College of American Pathologists NHS: National Health Service IHTSDO: International Health Terminology Standards Development Organization,Core contents,SNOMED CT,Applications,Electronic Heal
5、th Record Systems Computerized Provider Order Entry(CPOE) Knowledge databases used in clinical decision support systems(CDSS) Remote Intensive Care Unit Monitoring Laboratory Reporting Cancer Reporting Genetic Databases,SNOMED CT,Medical domains of the 100 Medline indexed papers in which a specific
6、medical domain has been described. (BMC Medical Informatics and Decision Making 2008, 8(Suppl 1):S2),SNOMED CT,Example: Mapping,Example: Encoding,Example: Standardization of Terminology,Part 3: OpenEHR,Objectives,Promote and publish formal specification,Promote and publish EHR architectures and mode
7、ls,Interoperable health informatics system,Maintain open source “reference” implementation,Implement EHR architectures into clinical use,Work closely with standards bodies,openEHR introduction,Definition: openEHR is an open standard specification in health informatics that describes the management a
8、nd storage, retrieval and exchange of health data in electronic health records (EHRs) Features: Patient-centric Lifelong Vendor-independent,Architecture of OpenEHR,OpenEHR Release 1.0.2,Two-level modeling of openEHR,openEHR EHR system implementation,applicability,Apply Store data Search data Share d
9、ata Not apply Control the exchanging flow,Integration of SNOMED CT into OpenEHR,HL7 v3 introduction,mission: provides standards for interoperability Features standard data, use reference information model (RIM) CDA, standardize clinical documents for exchange support healthcare workflows (V3 messagi
10、ng),RIM,applicability,Apply exchange information Control the exchanging flow Control the exchanging datas size Not apply Store data (we can store CDAs, but its not a best practice) Search data,Ongoing Biomedical Informatics Projects,Clinical Data and Sample is at the Core of Translational Medicine,C
11、linical Data,Clinical Practice,Biomarker,Biospecimen,Clinical Trial,LIMS,Genotypes,Domain Workspaces,Cross Cutting & Strategic Workspaces,Clinical Trials Management Systems (CTMS，临床实验管理系统) https:/cabig.nci.nih.gov/workspaces/CTMS/,Integrative Cancer Research (ICR，综合肿瘤研究) https:/cabig.nci.nih.gov/wor
12、kspaces/ICR,Tissue Banks & Pathology Tools (TBPT，组织库&病理学工) https:/cabig.nci.nih.gov/workspaces/TBPT,In Vivo Imaging （Vivo成像） https:/cabig.nci.nih.gov/workspaces/Imaging,Vocabularies&Common Data Elements(VCDE，词汇&公共数据元素) https:/cabig.nci.nih.gov/workspaces/VCDE,Architecture (体系构架) https:/cabig.nci.nih
13、.gov/workspaces/Architecture,Data Sharing & Intellectual Capital (DSIC，数据共享&智能财产) https:/cabig.nci.nih.gov/working_groups/DSIC_SLWG,Documentation & Training (D&T，文件&培训) https:/cabig.nci.nih.gov/working_groups/Training_SLWG,caBIG Workspaces,References and Standards,References used: caCORE (Cancer Com
14、mon Ontologic Representation Environment): caDSR (Cancer Data Standards Repository) NCI CBIIT (National Cancer institute Center for Biomedical Informatics and Information Technology),Collaboration with NCI and caBIG:Attended the caBIG annual meeting and visited caBIG in 2008 Two people from our cent
15、er attended the Boot Camp,Tissue Bank Information Management System,样本数据库信息管理系统 全面解决方案,Biobank Information Management Platform,Use Cases,Combined Tissue Bank Annotation from Operation Summary and Pathology Report,Medical Natural Language Processing,Difficulties of acquiring data and multiple times o
16、f entering,Direct connection to HIS、LIS and EMR Automatic transferring of data without entering by staffs Active reminding system for follow-up Automatic Data Query and Extraction Across Systems,Molecular classification database,Diagnostic tests database,Patients situation of treatment database,Pati
17、ent follow-up database,Sample database,Personalized treatment procedures,Clinical Information Enquiry System: The overall framework and subsystems,HIS database,LIS database,General enquiries,PACS database,D-QIS database,Clinical Information Enquiry System,Clinical Data Warehouse,R-MIM Model,Database
18、 Structure,Clinical Document （XML）,Database Records,SOA Service Bus,Clinical Data Warehouse,Clinical Document CDA Transfer Engine,Schema for Clinical Document,HL7 CDA Schema,Transfer Engine,Discharge Summary,CDA File,Mapping,Common Medical Terminology Service,Difficulties of Extracting Data,METHODS,
19、Models Performance,Models Performance,AUC(Lymphadenectasis):0.9517,AUC(Tumor Boundary):0.995,Models Performance,Biomedical Data Integration and Mining,Integration,Data Mining,Personalized Medicine Databases,Personalized MedicineDecision Support System,Medical Informatic,Bioinformatics,Translational
20、Medicine,Genomics,Disease and Gene Integration,GAD,COSMIC,Data Integration,Gene2Disease Databases,Genetic Polymorphisms 39910 Gene Mutations 1506545 19 Major Diseases Structured Gene Information 31412,Drug and Drug metabolism Study,Drug-Target-SNP Integration and Databases,SNP,Drug,Data Integration,
21、Drug-Target Polymorphism Databases,dbSNP,HapMap,Query Drug-Target-SNP,Drug Info,Target Info,SNP Info,Drug Metabolism,Mutation Information Integration,Extraction from Locus-specific databases,LSDB Addresses,Using WiKi Collect LSDB Addresses 1300 LSDB Classification of Geneslink to OMIM Database,http:
22、/129.89.44.120/twiki/bin/view,Mutation Information Extraction,Natural Language Processing Two LSDB Data Extration Alzheimer Disease & Frontotemporal Dementia Mutation Database Sarcomere Protein Gene Mutation Database 1725 mutation records,Mutation Association with Disease Phenotypes Standards Gene N
23、ames - HUGO Diseases（ICD-10） Mapping ICD-10 and MeSH, using keyword search Adopt SNOMED CT，Build Disease Ontologies,映射后的ICD-10疾病词汇表,Mutation Information Integration,Disease Related Unique Mutation Search Engine，DRUMS,Query,Genes, Diseases,Mutations, Sequences,More than 170,000 Mutations, 6000 genes,
24、External Links,Documents upload,By Genes By Diseases By Mutation types,http:/www.scbit.org/glif,Mutation Information Integration,DRUMS Query Results,Mutation Information Integration,Biomedical Informatics Systems for Translational Research,BioBank,EMR for Research EMR for Clinical Trial Follow-up In
25、formation Systems,Omic Databases LIMS Bioinformatics Analysis Platform,Database Establishment for Translational Research,DE-IDENTIFICATION,One way hash,Data Parsing,Data Parsing,Information collected during clinical care,Restructuring for research,Data export,SD Database,Access through secured onlin
26、e application,Informatics in EMR-based PGx Studies,Natural language processing (NLP) Machine learning & data mining,DNA Biobank,EMR,Informatics Approaches,Information Flow in Translational Medicine,New Therapeutic knowledge,Clinical Practice,Biospecimen,Clinical Data,High Throughput Research,CODATA
27、Task Group of Biomedical Ontology,提出生物医学数据互操作中的最关键问题 提出研究的重点方向 提出研究的思路与可能的技术路线 研讨预期的研究结果和可能的应用 研讨此研究的立项可能The interoperability of Biomedical Data Ontology Building Principles Data Sharing Strategies Technical Roadmap Expected Achievements Plan to make the first Discussion Meeting in 20112011 年内召开第一次研讨会，提出研究思路，形成核心团队，制定研究计划。,
