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Future Trends: Translational Informatics

Future Trends: Translational Informatics. James J. Cimino Chief, Laboratory for Informatics Development Mark O. Hatfield Clinical Research Center National Institutes of Health Institute for e-Health Policy, January 12, 2011. Genetics 101. Pathways. Replication. Translation. Phenome.

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Future Trends: Translational Informatics

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  1. Future Trends: Translational Informatics James J. Cimino Chief, Laboratory for Informatics Development Mark O. Hatfield Clinical Research Center National Institutes of Health Institute for e-Health Policy, January 12, 2011

  2. Genetics 101 Pathways Replication Translation Phenome Amino Acids Proteins DNA RNA Transcription Genome Folding Structures DNA

  3. The Genomic Timeline Human Genome DNA Structure Bacterial Genome 1953 2003 1995

  4. Translational Research Type 1 Type 2 “Type 0” Researchers Clinicians The application of research findings in one domain of study to another, (usually broader) domain.

  5. The Roles of Informatics Translational Informatics Biologic Knowledge Clinical Informatics Bioinformatics Clinical Knowledge

  6. Promise of Translational Informatics • Diseases predicted by genes • Effectiveness of prevention • Diseases indicated by activation • Appropriate testing • Drug dose, toxicity and interactions • Drug effectiveness

  7. Case Study • Patient with liver cancer and chest pain • Physician suspects pulmonary embolism • What is the best, least invasive test? • Will warfarin work to prevent further emboli? • What is the warfarin dose for this patient? • Will warfarin interact with other medications?

  8. How does the nose form? Phylogeny Phylogeny Ontogeny Definitely genetic Not a big protein! 5 types of tissue Billions of cells Coordination in time and space How many genes? How many variants?

  9. Genomics of a Single Disease DNA Hemoglobin A Structure Function -Pro-Glu-Glu- ....5......6......7..... ...16...17...18... -G-A-G- -Pro-Val-Glu- ....5......6......7..... ...16...17...18... -G-T-G- 1956 1953 2003

  10. Why is this so hard? Activation Denaturation Inhibition Mutations Other Genes Pathways Replication Translation Amino Acids DNA Proteins DNA RNA Transcription Folding Structures Environment Factors 3 billion base pairs in the human genome 100 trillion cells in the human body

  11. Types of Translational Informatics • Locating genetic sequences • Identifying genetic mutations • Tracking gene activation • Modeling protein folding • Simulating biologic pathways • Drug discovery • Personalized medicine

  12. The NIH and Translational Informatics • GenBank

  13. The NIH and Translational Informatics • Genome-Wide Association Studies (GWAS) • GenBank • Over 100 million sequences (100 billion bases)

  14. The NIH and Translational Informatics • GenBank • Over 100 million sequences (100 billion bases) • Genome-Wide Association Studies (GWAS) • study disease-specific genetic differences • Database of Phenome and Genome (dbGAP)

  15. The NIH and Translational Informatics • GenBank • Over 100 million sequences (100 billion bases) • Genome-Wide Association Studies (GWAS) • study disease-specific genetic differences • Database of Phenome and Genome (dbGAP) • archive of genotype-phenotype studies • Entrez

  16. The NIH and Translational Informatics • GenBank • Over 100 million sequences (100 billion bases) • Genome-Wide Association Studies (GWAS) • study disease-specific genetic differences • Database of Phenome and Genome (dbGAP) • archive of genotype-phenotype studies • Entrez • Cross-resource search tool for translational queries • ClinSeq

  17. The NIH and Translational Informatics • GenBank • Over 100 million sequences (100 billion bases) • Genome-Wide Association Studies (GWAS) • study disease-specific genetic differences • Database of Phenome and Genome (dbGAP) • archive of genotype-phenotype studies • Entrez • Cross-resource search tool for translational queries • ClinSeq • Complete sequencing of 1000 individuals • Biomedical Translational Research Information System (BTRIS)

  18. The NIH and Translational Informatics • GenBank • Over 100 million sequences (100 billion bases) • Genome-Wide Association Studies (GWAS) • study disease-specific genetic differences • Database of Phenome and Genome (dbGAP) • archive of genotype-phenotype studies • Entrez • Cross-resource search tool for translational queries • ClinSeq • Complete sequencing of 1000 individuals • Biomedical Translational Research Information System (BTRIS) • reusing clinical research data (1.5 billion rows of data) • Infobuttons

  19. The NIH and Translational Informatics • GenBank • Over 100 million sequences (100 billion bases) • Genome-Wide Association Studies (GWAS) • study disease-specific genetic differences • Database of Phenome and Genome (dbGAP) • archive of genotype-phenotype studies • Entrez • Cross-resource search tool for translational queries • ClinSeq • Complete sequencing of 1000 individuals • Biomedical Translational Research Information System (BTRIS) • reusing clinical research data (1.5 billion rows of data) • Infobuttons • delivering translational knowledge to the point of care

  20. Now What? • This biology stuff is complicated • Translational research is about applying findings from one domain to another domain • Translational informatics is the key to communicating data and knowledge between domains • Translational informatics research is a new field • We still need: • Informatics research support (NCTR? NCTI? NIBI?) • Training (extramural and intramural) • Support for collaborative efforts (CTSAs) • Centralization of resources for efficiency and equity

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