Technology and Computational Core
技术与计算核心
基本信息
- 批准号:10842887
- 负责人:
- 金额:$ 33.58万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-09-16 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:2019-nCoVAlgorithmsAmino Acid SequenceBase SequenceBiologicalBiological ModelsBloodBlood specimenCell SeparationCellsCellular Indexing of Transcriptomes and Epitopes by SequencingChemistryClinicalClonal ExpansionCollaborationsComplexComputer AnalysisComputer ModelsComputing MethodologiesCoronavirusDataData SetDevelopmentDiseaseEcosystemEmulsionsEngineeringEpitopesExperimental DesignsGene Expression ProfilingGenerationsGenetic TranscriptionGenomic approachGenomicsGoalsImmuneImmune responseImmunityImmunizationImmunizeImmunological ModelsImmunologistInfectionLungMachine LearningMapsMeasurementMembrane ProteinsMethodsModelingMolecularMusNaturePathway interactionsPhenotypePopulationPublicationsRNARecording of previous eventsReproducibilityResearchResearch PersonnelResearch Project GrantsResearch SupportSARS-CoV-2 variantScientistSpecimenStandardizationStructure of parenchyma of lungSystemT-LymphocyteTechniquesTechnologyTestingTherapeuticTissue SampleTissue-Specific Gene ExpressionTissuesVaccinesVariantVirusWorkantibody and antigen bindingcell typecomputer sciencecoronavirus vaccinedata integrationdesignexperimental analysisexperimental studyfuture pandemicgenomic datahuman subjectinnovationinsightmachine learning methodmultidisciplinarynext generationnovelpathogenpreventprogramsreceptorresponsesingle-cell RNA sequencingstemsuccessuniversal coronavirus vaccinevaccine strategyworking group
项目摘要
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.
项目概要核心 B
该计划项目的目标是汇集多学科团队来提供必要的信息
设计和测试下一代冠状病毒疫苗策略,该策略将具有最大可能
跨其他冠状病毒的广度。所有三个项目的结果将为泛冠状病毒疫苗的设计提供信息
对抗不断演变的 SARS-CoV-2 变种和其他冠状病毒,以阻止当前和预防未来的流行病。
这将通过三个动态和综合项目来完成,这些项目审查了各个关键方面
疫苗策略。技术和计算核心 B 将与每个部门密切互动,提供支持
其他研究人员,所有三个项目都从拟议的实验工作中获得最大的洞察力。基于
集中组织和血液处理、单细胞基因组学和 TCR 测序数据生成的需求,
和综合计算分析,我们假设拥有一个核心技术和计算
核心,而不是让每个项目独立工作,对于工作的成功至关重要
在此计划应用程序中提出,并将最大限度地比较和整合跨项目的数据。一个
由免疫学家、测序专家和计算生物学家组成的集中工作组是最好的方法
确保这项研究能够在最大程度地识别和使用适当的
计算方法。通过目标 1,核心 B 将通过提供专家支持所有三个研究项目
关于执行单细胞基因组学和 TCR 测序实验和分析的建议和帮助
从人类受试者收集的血液和组织样本以及从免疫小鼠的肺部收集的策略。这
核心人员提供的标准化框架将为所有实验增加严谨性和可重复性
消除任何可能出现的变化。核心 B 还将提供多变量方面的协作努力
免疫系统反应和抗原/抗体结合的建模(目标 2)。由于其复杂性
对病原体的免疫反应,我们从实验数据集中获得见解和原则的能力
所有三个项目产生的结果将通过综合计算分析和建模得到增强
拥抱综合系统视角。这种复杂性源于多种问题,包括:(a)
来自多个变量的伴随贡献共同控制观察到的响应,而不是任何单个变量
变量本身是决定性的; (b) 这些多变量贡献通常不是独立的,但是
相反,它们通常是互相关或反相关的; (c) 这些贡献本质上通常是非线性的。最多
标准统计技术通常会违反其中一个或多个问题,因此该核心的目的是
应用工程和计算机科学中产生的计算方法,包括“机器学习”
技术,实际上可以容纳其中任何或全部。最后,Core B将提供额外的帮助
如果/根据需要进行任何复杂的实验设计或分析。为了提高透明度,所有数据和分析
支持所有调查结果的框架将在接受出版后公开发布。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Alexandra-Chloe Villani其他文献
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