Very High Dimensional Visual Mining of the NCI Dataset

NCI 数据集的超高维可视化挖掘

• 批准号: 6443134
• 负责人: MICHAEL J MCMANUS
• 金额: $ 9.92万
• 依托单位: ANVIL INFORMATICS, INC.
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-05-01 至 2002-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6443134
• 关键词: antineoplastics; cancer information system; cell line; computer data analysis; computer system design /evaluation; data management; imaging /visualization /scanning; information retrieval; neoplasm /cancer pharmacology

There is a significant academic and commercial need for new tools that provide high dimensional data visualizations, coupled to analytical data mining techniques. We believe that visualization is the interface to analysis and provides guidance in the discovery process. As a major aim, we will investigate and evaluate new visualization tools, some of which are proprietary, capable of displaying an arbitrary number of dimensions, some of which are proprietary, capable of displaying an arbitrary number of dimensions of data simultaneously. To do this, we will use the large public NCI DIS compound dataset that has been tested against a battery of 60 cancer cell lines. In addition to tool evaluation using this dataset, a lesser aim will be knowledge discovery in the dataset. We propose calculation of the Molconn-Z chemical descriptors and the combined data mining of these descriptors. and associated cell line data. This activity is aimed at the discovery of new compound cancer activity patterns that may be useful in a clinical setting. In a follow on Phase II research study, we will integrate the selected visualization and analytic tools into a robust integrated data mining package for commercial use. PROPOSED COMMERCIAL APPLICATIONS: The Specific Aims of this Phase I proposal will allow us to evaluate the commercial potential of high dimensional visualization and analysis tools using the publicly available NCI DIS dataset, as well as data mine this dataset for potential new discoveries.

有一个显着的学术和商业需要新的工具，提供高维数据可视化，再加上分析数据挖掘技术。我们相信可视化是分析的接口，并在发现过程中提供指导。作为一个主要目标，我们将研究和评估新的可视化工具，其中一些是专有的，能够显示任意数量的维度，其中一些是专有的，能够同时显示任意数量的数据维度。为此，我们将使用大型公共NCI DIS化合物数据集，该数据集已针对60种癌细胞系进行了测试。除了使用该数据集进行工具评估之外，次要目标是数据集中的知识发现。我们建议计算Molconn-Z化学描述符和这些描述符的组合数据挖掘。和相关的细胞系数据。这项活动旨在发现可能在临床环境中有用的新的化合物癌症活动模式。在第二阶段的后续研究中，我们将把选定的可视化和分析工具集成到一个强大的集成数据挖掘包中，以供商业使用。拟议的商业应用：第一阶段提案的具体目标将使我们能够使用公开可用的NCI DIS评估高维可视化和分析工具的商业潜力 数据集，以及数据挖掘这个数据集的潜在新发现。