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Bioinformatics and Biostatistics Data Analysis Core

Bioinformatics and Biostatistics Data Analysis Core
生物信息学和生物统计学数据分析核心
批准号:
10478004
负责人:
Sohrab Shah
金额:
$32.83万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-08-13 至 2025-07-31
关键词:
AchievementAddressAnimalsBackBioinformaticsBiological Specimen BanksBiometryCDK4 geneCellsChromosomal InstabilityChromosomesClinical DataClinical ResearchClinical TrialsCluster AnalysisCollectionComputational BiologyComputer AnalysisComputing MethodologiesCustomDNADNA RepairDNA Repair DisorderDNA sequencingDataData AnalysesData CollectionData SourcesDatabasesDefectDepositionDevelopmentDiseaseEnsureEstrogen receptor positiveFormulationGeneticGenomic InstabilityGenomicsGoalsHeterogeneityHigh Performance ComputingHormonesHumanHuman ResourcesImmuneImmunocompetentInfrastructureLaboratory ResearchLengthLinkMaintenanceMediatingMemorial Sloan-Kettering Cancer CenterMetadataMetastatic breast cancerMethodsModelingMolecularMutationPathologyPatientsPeriodicityPhenotypePrevalenceProceduresProspective cohort studyRNAReproducibilityResearchResearch DesignResearch PersonnelResearch Project GrantsResistanceResourcesSample SizeSamplingScientistServicesSingle Nucleotide PolymorphismSpace ModelsSpecimenStatistical AlgorithmStatistical Data InterpretationStatistical MethodsStratificationTimeTime Series AnalysisValidationVariantVisualizationWorkanalysis pipelinebasebioinformatics toolbiomarker developmentbiomarker validationcBioPortalcancer genomecancer genomicscell typeclinical careclinical trial analysisclinically significantcomputerized data processingcomputerized toolsdata integrationdesigndiverse dataexomeexperiencefitnessfollow-upgenome sequencinggenomic datagenomic signaturehomologous recombinationinnovationlaboratory experimentmalignant breast neoplasmmembermouse modelmultimodalitymultiple data sourcesneoplastic cellnext generation sequencingnovelonline resourcepatient derived xenograft modelpreclinical studyresearch studysingle cell sequencingsingle-cell RNA sequencingsuccesstelomeretooltranscriptometranscriptome sequencingtranslational goaltumortumor-immune system interactionsvalidation studieswhole genome

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ABSTRACT The Biostatistics and Computational Genomics Core will provide support in statistical and computational analysis of sequencing data, biomarker development and validation, pre-clinical study design and analysis to meet the needs of the SPORE Research Projects and interact with other Cores and institutional resources to achieve the scientific and translational purposes of the SPORE. The Research Projects in this SPORE require a broad range of statistical and bioinformatics expertise, including tools for the analysis and visualization of whole genome sequencing and single cell sequencing data. The Core will provide a team of dedicated personnel with extensive experience and strong track record of developing innovative statistical and computational methods. We will maintain and expand current tools and pipelines to assist the design and analysis of the SPORE research projects, and provide centralized support for data collection, processing, quality assessment, and normalization procedures to facilitate data integration and downstream analysis and visualization. Importantly, the core will devote significant effort in developing innovative computational tools that aim to detect, quantify, and track genomic signatures of specific DNA repair defects and/or genetic instability at the tumor bulk and single cell levels. In addition, the Core will synergize with the current infrastructure available at Memorial Sloan Kettering Cancer Center to provide the SPORE investigators not only with the state-of-the-art computational biology methods, but also with novel computational tools to address specific analytical challenges germane to the success of the SPORE Research Projects.
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Exploiting markers of genomic instability in high-risk pre-invasive ovarian cancer
Bioinformatics and Biostatistics Data Analysis Core
Bioinformatics and Biostatistics Data Analysis Core
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