Data Analysis Core

数据分析核心

基本信息

批准号：
10201588
负责人：
Jeffrey M Spraggins
金额：
$ 62.31万
依托单位：
VANDERBILT UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-24 至 2022-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10201588
关键词：
3-Dimensional Address Algorithms Atlases Automation Biological Biological Assay Calibration Complex Computer software Confidence Intervals Cues Data Data Analyses Data Set Development Dimensions Disease Documentation Feedback Glean Goals High Performance Computing Human BioMolecular Atlas Program Image Imaging technology Ions Lead Link Magnetic Resonance Imaging Maps Mass Spectrum Analysis Mathematics Measurement Measures Medical Imaging Memory Methodology Methods Microscopy Mining Mission Modality Molecular Molecular Analysis Multilingualism Multimodal Imaging Normal tissue morphology Phase Play Process Reporting Research Personnel Resolution Sampling Source Specific qualifier value System Technology Tissues Training Universities Variant Vendor Visualization Work base cell type computational platform computerized data processing computing resources data analysis pipeline data exchange data mining data quality data visualization driving force experience file format high dimensionality human tissue inclusion criteria insight microscopic imaging molecular imaging multimodality novel strategies open source parallelization reconstruction scaffold spatial integration spectrograph

3-Dimensional Address Algorithms Atlases Automation Biological Biological Assay Calibration Complex Computer software Confidence Intervals Cues Data Data Analyses Data Set Development Dimensions Disease Documentation Feedback Glean Goals High Performance Computing Human BioMolecular Atlas Program Image Imaging technology Ions Lead Link Magnetic Resonance Imaging Maps Mass Spectrum Analysis Mathematics Measurement Measures Medical Imaging Memory Methodology Methods Microscopy Mining Mission Modality Molecular Molecular Analysis Multilingualism Multimodal Imaging Normal tissue morphology Phase Play Process Reporting Research Personnel Resolution Sampling Source Specific qualifier value System Technology Tissues Training Universities Variant Vendor Visualization Work base cell type computational platform computerized data processing computing resources data analysis pipeline data exchange data mining data quality data visualization driving force experience file format high dimensionality human tissue inclusion criteria insight microscopic imaging molecular imaging multimodality novel strategies open source parallelization reconstruction scaffold spatial integration spectrograph

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项目摘要

Project Summary The VU-BIOMIC Data Analysis Core (DAC) is tasked with both pre-analytical and analytical challenges. The investigators of the DAC have broad range of experience working with high-dimensional imaging mass spectrometry data sets, even leading the field in new methodologies to process such data. In addition, the DAC team has pioneered methods to combine high spatial resolution microscopy and 3-dimensional data sets with IMS. However, BIOMIC will require that the DAC architect a platform that integrate all of the pre-analytical and analytical computational approaches into a complete computational platform capable of processing the data generated by the Characterization pipeline efficiently. A primary driving force behind all work carried out will be automation of the reconstruction and subsequent analysis. This will allow plug-and-play analysis of new datasets as they are generated. As the experimental workflow is expansive, it is important that the DAC provide rapid feedback of metrics to track data quality and provide analyses that lead to biological insight.

项目摘要 VU-BIOMIC数据分析核心（DAC）的任务是分析前和分析挑战。这 DAC的研究人员具有与高维成像质量合作的广泛经验光谱数据集，甚至在新方法中引导该领域来处理此类数据。另外，DAC 团队采用了率先使用的方法，可以将高空间分辨率显微镜和3维数据集与 ims。但是，生物局将要求DAC架构师一个平台，该平台整合了所有分析和分析计算方法进入一个完整的计算平台，能够处理数据由表征管道有效生成。所有进行的所有工作背后的主要驱动力将是重建和后续分析的自动化。这将允许对新的插件分析生成数据集。由于实验工作流程很大，因此DAC很重要提供指标的快速反馈，以跟踪数据质量并提供导致生物学见解的分析。