Technology and Computational Core
Technology and Computational Core
批准号:
10328118
负责人:
Alexandra-Chloe Villani
金额:
$174.61万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-09-16 至 2024-08-31
关键词:
2019-nCoVAlgebraAlgorithmsAmino Acid SequenceBase SequenceBiologicalBiological ModelsBloodBlood specimenCellsCellular Indexing of Transcriptomes and Epitopes by SequencingChemistryClinicalClonal ExpansionCollaborationsComplexComputer AnalysisComputer ModelsComputing MethodologiesCoronavirusDataData AnalysesData SetDevelopmentDiseaseEcosystemEmulsionsEngineeringEnsureEpitopesExperimental DesignsFutureGene Expression ProfilingGenerationsGenetic TranscriptionGenomic approachGenomicsGoalsImmuneImmune responseImmunityImmunizationImmunizeImmunological ModelsImmunologistInfectionLungMachine LearningMeasurementMembrane ProteinsMethodsModelingMolecularMusNaturePathway interactionsPhenotypePopulationPublicationsRNARecording of previous eventsReproducibilityResearchResearch PersonnelResearch Project GrantsResearch SupportSARS-CoV-2 variantScientistSpecimenStandardizationStructure of parenchyma of lungSystemT-LymphocyteTechniquesTechnologyTestingTherapeuticTissue SampleTissue-Specific Gene ExpressionTissuesVaccinesVariantVirusWorkantigen antibody bindingbasecell typecomputer sciencecoronavirus vaccinedata integrationdesignexperimental analysisexperimental studygenomic datahuman subjectinnovationinsightmachine learning methodmultidisciplinarynext generationnovelpandemic diseasepathogenpreventprogramsreceptorresponsesingle cell analysissingle-cell RNA sequencingstemsuccessuniversal coronavirus vaccineworking group
中文摘要
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英文摘要
PROJECT SUMMARY CORE B
The goal of this Program Project is to bring together a multi-disciplinary team to produce information necessary
for the design and testing of the next-generation of CoV vaccine strategies that will have the greatest possible
breadth across other CoVs. Results from all three projects will inform design of Pan-Coronavirus vaccines
against evolving SARS-CoV-2 variants and other coronaviruses to stem current and prevent future pandemics.
This will be accomplished through three dynamic and integrative projects examining various key aspects of
vaccine strategies. The Technology and Computational Core B will support, in close interaction with each of the
other investigators, all three Projects to gain maximal insight from the proposed experimental work. Based on
the need for centralized tissue and blood processing, single-cell genomics and TCR sequencing data generation,
and integrative computational analyses, we hypothesized that having a central Technology and Computational
Core, as opposed to having each project working independently, will be critical to the success of the work
proposed in this Program application and will maximize comparisons and integration of data across projects. A
centralized working group of immunologists, sequencing experts, and computational biologists is the best way
to ensure that this research will be properly carried out with maximal identification and use of appropriate
computational methods. Through Aim 1, Core B will support all three Research Projects by providing expert
advice and assistance on executing single-cell genomics and TCR sequencing experimental and analytical
strategies of blood and tissue specimens collected from human subjects and lung from immunized mice. The
standardized frameworks provided by the Core staff will add rigor and reproducibility to all experiments by
removing any variation that might otherwise arise. Core B will also provide collaborative efforts on multi-variate
modeling of immune system response and antigen/antibody binding (Aim 2). Because of the complexity of
immune responses to pathogens, our ability to gain insights and principles from the experimental datasets
generated across all three Projects will be enhanced by integrative computational analysis and modeling
embracing an integrative systems perspective. This complexity derives from diverse issues including: (a)
concomitant contributions from multiple variables together govern observed responses, rather than any single
variable being determinative by itself; (b) these multi-variate contributions are generally not independent, but
instead are typically co- or anti-correlated; and (c) these contributions often are non-linear in nature. Most
standard statistical techniques typically violate one or more of these issues, so the purpose of this Core is to
apply computational approaches arising from engineering and computer science, including “machine learning”
techniques, that can in fact accommodate any or all of them. Finally, Core B will provide additional assistance
for any complicated experimental design or analysis if/as needed. To aid with transparency, all data and analysis
frameworks supporting all findings will be made publicly available upon acceptance for publication.
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Technology and Computational Core
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批准号:10842887
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项目类别:
-
资助金额:$33.58万
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财政年份:2021
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负责人:Alexandra-Chloe Villani
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依托单位:
海外基金