Array Tomography Visualization and Analysis Software
Array Tomography Visualization and Analysis Software
批准号:
8780498
负责人:
David Peter Lenzi
金额:
$29.64万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-22 至 2015-12-31
关键词:
AgeAlgorithmsAlzheimer&aposs DiseaseArchitectureBiological Neural NetworksBrainCell NucleusColorCommunitiesComplexComputer softwareComputersDataData AnalysesData SetDetectionDevelopmentDimensionsDiseaseDisease ProgressionDue ProcessGenerationsHumanImageImageryIndividualJavaLibrariesLight MicroscopeLocationMetadataMethodsMetricMolecularNerve DegenerationNeurodegenerative DisordersNeurosciencesNoiseOperating SystemOutputParkinson DiseasePathologyPhasePopulationProcessProteomicsProtocols documentationPublicationsQuality ControlRelative (related person)ResearchResearch PersonnelResolutionRunningSamplingServicesSimulateSpeedSpottingsStagingStem cellsStretchingSynapsesSystemTechnologyTherapeuticThree-Dimensional ImageTissuesUncertaintyValidationVisualVisualization softwareanticancer researchassay developmentbasecomputing resourcesdensitydesigneffective therapyfallsheuristicsimage processingimaging modalityinterestneural circuitpublic health relevancereconstructionstatisticssuccesstechnology developmenttomographytoolvibration
中文摘要
描述(由申请人提供):神经退行性疾病是人类疾病中最昂贵、最具破坏性和治疗效果最差的疾病之一,可以说是因为它们没有得到很好的理解。阵列断层扫描是一种新的组织成像方法,在所有三个维度上的分辨率足以解析单个突触,并在整个大样本中提供多个(目前约40个)分子成分的定量表征。阵列层析成像数据能够在三维组织结构的背景下描述神经网络。我们相信这些数据将使研究人员能够开始理解神经回路的正确功能,更重要的是,开始理解各种神经退行性过程是如何出现和发展的。然而,阵列层析成像复杂且昂贵,自2007年首次发表以来,在相对较少的研究中使用(Micheva和Smith, 2007)。Aratome目前为研究界提供阵列断层扫描服务。本申请提出了一种软件应用程序的开发,该软件应用程序可自动组装多通道图像卷并提供分析这些数据的工具。数据的组装和分析是目前生产和使用高质量阵列层析成像数据的瓶颈。该包将在内部使用,并作为产品提供给研究界。
英文摘要
DESCRIPTION (provided by applicant): Neurodegenerative diseases are among the most expensive, disruptive, and least well treated of human maladies, arguably because they are not well understood. Array Tomography is a new method for tissue imaging with resolution in all three dimensions sufficient to resolve individual synapses and provide quantitative characterization of multiple (currently ~40) molecular constituents, throughout large samples. Array Tomography imaging data enable description of neural networks in the context of the three-dimensional tissue architecture. We believe such data will enable researchers to begin to comprehend the proper function of neural circuits and, importantly, to begin to understand how it is that the various neurodegenerative processes present and progress. Array Tomography is, however, complex and expensive, and has been used in relatively few studies following the first publication in 2007 (Micheva and Smith, 2007). Aratome is currently offering Array Tomography services to the research community. The present application proposes the development of a software application that automates the assembly of the multi- channel image volumes and provides tools to analyze those data. Assembling and analyzing data constitute the current bottleneck in producing and using high quality Array Tomography data. The package will be used internally and made available as a product to the research community.
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