FLOW CYTOMETRY DATA ANALYSIS BY EXPERT SYSTEMS

由专家系统进行流式细胞术数据分析

• 批准号: 3199068
• 负责人: GARY C SALZMAN
• 金额: $ 28.44万
• 依托单位: UNIVERSITY OF CALIF-LOS ALAMOS NAT LAB
• 依托单位国家: 美国
• 财政年份: 1990
• 资助国家: 美国
• 起止时间: 1990-12-07 至 1993-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3199068
• 关键词: CD antigens; artificial intelligence; classification; computer data analysis; computer graphics /printing; computer program /software; computer system design /evaluation; flow cytometry; lymphocyte; mathematical model; monoclonal antibody; personal computers; statistics /biometry

The broad, long term objective of this proposal is to develop user-friendly, intelligent software that will enable biologists to analyze their multivariate now cytometry data more efficiently and more effectively. Flow Cytometers can now collect eight or more measurements per cell and biochemists and cell biologists have devised markers to take advantage of this multiparameter capability. The software to enable biologists to easily analyze this multivariate data is only now beginning to be developed. This proposal addresses the needs of investigators doing basic cell biology work and clinicians needing rapid and thorough analyses of their multivariate flow cytometry data. Specific Aim 1 is focused on the development of device independent software for interactive, exploratory analysis of multivariate flow cytometry data. The software will use a mouse and menu user interface so that the user will not have to read bulky manuals. The program will include two and three dimensional dynamic color graphics. It will incorporate a statistical expert system called GRAPH HELPER to assist the user in choosing the best set of displays to examine. In Specific Aim 2, an expert system will be developed that incorporates the knowledge of a statistician and that of a biologist to assist in the automatic processing of many datasets of multivariate flow cytometry data. The ANALYST expert system will contain separate knowledge bases for statistical expertise and biological expertise. The statistician knowledge base will include rules and facts about hypothesis testing, cluster analysis, dimensionality reduction, probability modeling and two and three dimensional graphical display techniques. The biologist knowledge base will at first include rules and facts governing human differentiation antigen clusters and the fluorescent monoclonal antibodies used to detect them. It will later include knowledge about other specific biological systems. Specific Aim 3 is focused on the investigation of several approaches to partitioning multivariate flow cytometry data. Parametric clustering schemes using the K-means algorithm and the Mahalanobis distance metric will be investigated along with several nonparametric approaches. Various techniques will be examined for efficiently starting the clustering process and for determining the correct number of clusters. Classification and Regression Tree (CART) algorithms will be investigated for partitioning multivariate flow cytometry data after an initial clustering. Clustering methods will be developed to run on the LANL Connection Machine so that data from large numbers of cells can be included in a cluster analysis during an interactive session with the user.

该提议的广泛，长期目标是发展 用户友好，智能软件将使生物学家能够 现在，更有效地分析其多变量的细胞仪数据 有效地。 流式细胞仪现在可以收集八个或多个测量值 每个细胞和生物化学家和细胞生物学家已经设计了标记 该多参数能力的优势。 启用软件 生物学家才能轻松分析此多元数据，直到现在才开始 要开发。 该提议满足了调查人员的需求 进行基本的细胞生物学工作和临床医生需要快速，彻底的 对其多元流式细胞仪数据的分析。 具体目标1是 专注于开发设备独立软件的 多元流式细胞仪数据的交互式，探索性分析。 该软件将使用鼠标和菜单用户界面，以便用户 不必阅读笨重的手册。 该程序将包括两个， 三维动态颜色图形。 它将结合 统计专家系统称为Graph Helper来协助用户 选择最佳的显示器集。 在特定的目标2中 将开发专家系统，以结合一个知识 统计学家和生物学家的协助自动 处理多元流式细胞仪数据的许多数据集。 这 分析师专家系统将包含单独的知识库 统计专业知识和生物专业知识。 统计学家 知识库将包括有关假设检验的规则和事实， 聚类分析，降低降低，概率建模和两个 和三维图形显示技术。 生物学家 知识基础最初将包括管理人类的规则和事实 分化抗原簇和荧光单克隆 用于检测它们的抗体。 稍后将包括有关的知识 其他特定的生物系统。 具体目标3专注于 研究分区多元流的几种方法 细胞仪数据。使用K-均值算法的参数聚类方案 并将研究Mahalanobis距离度量标准 几种非参数方法。 将检查各种技术 有效地开始聚类过程并确定 正确数量的群集。 分类和回归树（购物车） 将研究算法以分区多元流 初始聚类后的细胞仪数据。 聚类方法将是 开发用于在LANL连接机上运行，​​以便来自大的数据 可以在 与用户交互式会话。