Platform for High-Throughput Analysis of Integrated Cancer Imaging and Multi-Omics Data
Platform for High-Throughput Analysis of Integrated Cancer Imaging and Multi-Omics Data
批准号:
9568920
负责人:
Patricia Buendia
金额:
$22.38万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-11 至 2018-06-10
关键词:
BioinformaticsBiologicalBiologyBiometryCatalogsClassificationCommunitiesComplexComputer softwareComputersControlled VocabularyCorrelation StudiesDataData AnalysesData SetData SourcesData Storage and RetrievalDetectionDimensionsDocumentationEnsureFeedbackGene ChipsGlioblastomaGoalsGraphImageIndividualIngestionMalignant NeoplasmsMeasurementMedical ImagingMetadataMethodsModelingMolecularOntologyPathway interactionsPhasePhenotypeProcessProteomeProteomicsProtocols documentationQuality ControlReportingResearchRetrievalSamplingSliceSoftware EngineeringSourceStructureSystemSystems AnalysisTechniquesTechnologyTestingThe Cancer Genome AtlasVocabularybasecancer imagingdata formatdata integrationdata visualizationdatabase schemadesignexperimental studygenetic signaturegenome sequencinggraphical user interfacehigh throughput analysisimaging modalityimprovedin vivo imaginginnovative technologiesinsightknowledge basemetabolomemetabolomicsmultiple omicsnext generation sequencingprecision medicineproduct developmentprototypepublic health researchradiomicsrepositorytooltranscriptometranscriptomicstumoruser centered design
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Cancer studies increasingly include medical imaging and measurements from multiple omics techniques. The main impetus for data integration is that, through these integrated data sets, an improved understanding of the underlying biology is obtained to be better able to predict a phenotype and to gain further insight into mechanistic aspects of the system at the molecular level. In this project we propose to develop innovative technologies to integrate metabolite data with multi-omic (metabolomics, proteomics and transcriptomics) and cancer imaging data to enable the detection of subtler and more complex associations among variables, with the medical imaging and the metabolome providing phenotypic measurements to which we can anchor the global measurements of the transcriptome and proteome. The proposed Multi-omics and Imaging Data Analysis System (MIDAS) will provide for the ingestion, annotation, quality control, and analysis of in vivo imaging data combined with ex vivo -omics data to advance research in cancer. MIDAS is aimed at helping the cancer and overall public health research communities advance faster towards the larger goal of precision medicine through valid and reliable data harmonization of metabolomics, transcriptomics, proteomics, radiomics and other imaging data.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
In Vivo Cluster AI Prediction (CLAIRE) of COVID-19 Disease Progression
-
批准号:10256828
-
项目类别:
-
资助金额:$24.87万
-
财政年份:2021
-
负责人:Patricia Buendia
-
依托单位:
SBIR PHASE II TOPIC "Scalable Automated Brain Tumor Segmentation"
-
批准号:8947908
-
项目类别:
-
资助金额:$100.0万
-
财政年份:2014
-
负责人:Patricia Buendia
-
依托单位:
Reconstructing Pathways of HIV Drug Resistance
-
批准号:7694493
-
项目类别:
-
资助金额:$5.33万
-
财政年份:2008
-
负责人:Patricia Buendia
-
依托单位:
海外基金