Collaborative Research: Biological Shape Spaces, Transforming Shape into Knowledge

合作研究：生物形状空间，将形状转化为知识

• 批准号: 1053130
• 负责人: Rolf Mueller
• 金额: $ 26.06万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1053130&HistoricalAwards=false
• 关键词: Collaborative; Research; Biological; Shape; Spaces

Collaborative Research: Biological Shape Spaces, Transforming Shape into KnowledgeThis project will develop a framework to represent, analyze and interpret shapes extracted from images, supporting a wide range of biological investigations. The primary objectives are: (1) to develop a mathematical framework and computational tools for the quantification and analysis of shapes; (2) to integrate these computational models with machine learning and statistical inference methods to enable new discoveries, transforming imaging data into biological knowledge; (3) to deliver novel quantitative methodologies for shape analysis that start from a biological premise, rather than a purely geometric one. The aim is thus not only to quantitatively describe shape, but to develop methods for linking morphological variation to its underlying biological causes. To ensure that the project focuses on methods that are most promising to biology with significant breadth of application, model and tool development will be guided and supported by a set of diverse case studies, ranging from the sub-cellular to organismal scales. Shape represents a complex and rich source of biological information that is fundamentally linked to underlying mechanisms and function. However, shape is still often examined on a qualitative basis in many disciplines in biology, an approach that is time consuming and prone to human subjectivity. While ad hoc quantitative methods do exist, they are often inaccessible to non-experts and do not easily generalize to a wide variety of problems. The inability of biologists to systematically link shape to genetics, development, environment, function and evolution often precludes advances in biological research spanning diverse spatial and temporal scales, from the movement of molecules within a cell to adaptive changes in organismal morphology. The primary goal of this project is to develop a new suite of widely applicable quantitative methods and tools into the study of biological shape to address the significant need for consistent and repeatable analysis of shape data.

协作研究：生物形状空间，将形状转化为知识的项目将开发一个框架，以代表，分析和解释从图像中提取的形状，支持广泛的生物学研究。主要目标是：（1）开发用于量化和分析形状的数学框架和计算工具； （2）将这些计算模型与机器学习和统计推断方法相结合，以使新发现将成像数据转换为生物学知识； （3）提供新的定量方法，用于形状分析，而不是从生物学前提开始，而不是纯几何方法。因此，其目的不仅是为了定量描述形状，而且是开发将形态变异与其潜在生物学原因联系起来的方法。 为了确保该项目的重点是最有希望的生物学方法，其应用，模型和工具开发的广度将受到一系列不同的案例研究的指导和支持，范围从子细胞到有机量表。形状代表着复杂而丰富的生物信息来源，与基本机制和功能从根本上联系起来。但是，在生物学的许多学科中，仍然经常在定性的基础上对形状进行研究，这种方法耗时且容易受到人类主观性的影响。尽管确实存在临时定量方法，但它们通常是非专家无法访问的，并且不容易将其推广到各种各样的问题。生物学家无法系统地将形状与遗传学，发育，环境，功能和进化的形状联系起来，通常无法在生物学研究中的进步，从分子在细胞内的分子运动到生物形态学的适应性变化。该项目的主要目标是将新的一组广泛适用的定量方法和工具开发到生物形状的研究中，以解决对形状数据一致且可重复分析的重要需求。