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: 1053036
• 负责人: Charless Fowlkes
• 金额: $ 28.44万
• 依托单位: University of California-Irvine
• 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=1053036&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.

该项目将开发一个框架来表示、分析和解释从图像中提取的形状，支持广泛的生物研究。主要目标是：(1)开发用于形状量化和分析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理方法相结合，以实现新的发现，将成像数据转化为生物学知识；(3)为形状分析提供新颖的定量方法，这些方法从生物学的前提出发，而不是纯粹的几何前提。因此，目的不仅是定量地描述形状，而且要发展方法，将形态变化与其潜在的生物学原因联系起来。为了确保该项目侧重于最有希望应用于生物学的方法，模型和工具的开发将由一系列不同的案例研究指导和支持，范围从亚细胞到有机尺度。形状代表了一个复杂而丰富的生物信息来源，从根本上与潜在的机制和功能联系在一起。然而，在生物学的许多学科中，形状仍然经常在定性的基础上进行检验，这种方法既耗时又容易受到人类主观性的影响。虽然确实存在专门的定量方法，但非专家往往无法使用这些方法，而且不容易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、功能和进化联系起来，这往往阻碍了跨越不同空间和时间尺度的生物学研究取得进展，从细胞内分子的运动到生物体形态的适应性变化。该项目的主要目标是开发一套新的广泛适用的定量方法和工具来研究生物形状，以满足对形状数据进行一致和可重复分析的重大需求。