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Comparative Genomics of Non-Coding Regions to Facilitate Translational Research

Comparative Genomics of Non-Coding Regions to Facilitate Translational Research
非编码区域的比较基因组学促进转化研究
批准号:
7806572
负责人:
INNA DUBCHAK
金额:
$78.5万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-04-15 至 2013-03-31
关键词:
Academic Medical CentersAddressAdoptedAdoptionAffectAgeAnatomyAnimalsArchitectureArtsAsthmaAutomobile DrivingBase SequenceBiologicalBiological ModelsBiologyBiomedical ComputingBiomedical ResearchCardiovascular DiseasesClassificationClinicalClinical DataClinical InvestigatorClinical ResearchCollaborationsCommunitiesCompanionsComputer softwareComputing MethodologiesConsentDNA BindingDNA SequenceDataData SetDatabasesDevelopmentDiabetes MellitusDisciplineDiseaseDisease ProgressionDisease modelDoctor of MedicineDoctor of PhilosophyEmploymentEngineeringEnsureEpigenetic ProcessFrequenciesFruitFunctional RNAFutureGene ExpressionGenerationsGeneticGenetic PolymorphismGenetic TranslationGenomeGenomicsGoalsHealthHealth SciencesHealthcareHealthcare SystemsHeterogeneityHospitalsHumanHuman GenomeHuman Genome ProjectHypertensionInformaticsInformation TechnologyIntellectual PropertyKnowledgeLaboratoriesLeadershipLicensingMajor Depressive DisorderMapsMeasurementMedicalMethodologyMethodsModelingObesityOntologyOrganismPatientsPattern RecognitionPhenotypePhysiologyPlayPopulationPrincipal InvestigatorProcessProgram DescriptionPropertyProteomicsPublic HealthPublic Health SchoolsQuantitative Trait LociRecording of previous eventsRegulator GenesResearchResearch DesignResearch PersonnelResourcesRheumatoid ArthritisRoleSamplingScienceSequence AnalysisSolutionsStructureSystemTechnologyTestingTextTherapeuticTimeTime Series AnalysisTraining ActivityTranslatingTranslational ResearchTranslationsUnderrepresented MinorityUnited States National Institutes of HealthUpdateUrticariaVariantWomanWorkbasebiocomputingbiological researchbiomedical informaticsclinical careclinical practiceclinically relevantcomparativecomparative genomicscomputer frameworkcomputerized data processingcomputing resourcesdata integrationdatabase structuredesigngenome-widehealth care deliveryhuman diseasehuman morbidityimage processingimprovedinnovationinsightinterdisciplinary collaborationknowledge basemedical schoolsmodels and simulationmortalitymultidisciplinarynervous system disordernovelnovel diagnosticspatient populationprognosticprogramsresponsestructural biologysuccesstooluser-friendlyvirtualweb site

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DESCRIPTION (provided by applicant): There is increasing evidence that variations in non-coding sequences that regulate gene expression play an important role in human disease. However, the identification of non-coding, regulatory polymorphisms contributing to disease is limited by our inability to identify which variants reside within gene regulatory sequences. Multiple recent studies indicate that highly conserved non-coding regions identified by comparative sequence analysis often possess gene regulatory activity. Thus, sequence conservation alone can prioritize noncoding sequences for gene regulatory function. While it is reasonable to expect that variations in highly conserved non-coding regions are more likely to be deleterious, very little research has been directed to validate this hypothesis in clinical populations. Accordingly, the goal of this proposal is to investigate the utility of comparative genomics for the prioritization of functional non-coding sequence variations in several disease models and to build computational resources enabling the employment of this strategy by clinical investigators. To accomplish this, we will first classify non- coding sequence variations based on a range of comparative genomic criteria to estimate their likelihood of deleteriousness. Collaboration with i2b2 clinical investigators will enable us to test the validity of this classification in a clinical study of asthma. Building on the success of VISTA, our suite of comparative genomic tools already widely used by the biomedical community, we will develop a user-friendly "clinical comparative genome portal" to automate this process. Finally, integration of the portal into i2b2's Hive architecture and clinical research chart will enable clinical investigators to exploit the synergies of computational and clinical sequence-based data in their analysis of i2b2 rich clinical databases and to accelerate the translation of clinical genetic data into functional insights. To facilitate the dissemination and adoption of the comparative portal, in coordination with i2b2 we will organize online and offline training activities specifically targeted at clinical users. PUBLIC HEALTH REVELANCE: Genetic studies of common human diseases will become increasingly frequent in the near future, thanks to advances in genomic science and sequencing technologies. Common diseases, such as diabetes and cardiovascular disease, are among the major causes of human morbidity and mortality. Novel computational approaches are needed to help translate the genetic information obtained in such studies into functional information that can be used to understand the mechanisms of disease and develop new diagnostic and therapeutic approaches. In this proposal, we will use our expertise with comparative sequence analysis to develop a computational platform to help integrate computational and clinical data based on the sequence of the human genome and accelerate the translation of genetic findings into functional and medical insights. This platform will be widely available to clinical investigators through the NIH-supported i2b2 clinical research chart.
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Comparative Genomics of Non-Coding Regions to Facilitate Translational Research
Comparative Genomics of Non-Coding Regions to Facilitate Translational Research
Comparative Genomics of Non-Coding Regions to Facilitate Translational Research
Comparative genomics with the VISTA/LAGAN computational system
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