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，支持广泛的生物学研究。主要目标是：(1)为形状的量化和分析开发一个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)提供从生物学前提而不是纯粹的几何前提开始的形状分析的新的定量方法。因此，其目的不仅是定量描述形状，而且开发将形态变化与其潜在的生物学原因联系起来的方法。为了确保该项目侧重于对生物学最有希望的方法，并具有广泛的应用范围，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，从亚细胞到生物尺度。形状代表了复杂而丰富的生物信息来源，这些信息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，形状仍然经常被定性地研究，这是一种耗时且容易受到人类主观性影响的方法。虽然确实存在特别的定量方法，但非专家往往无法使用这些方法，而且不容易将其推广到各种问题。生物学家无法系统地将形状与遗传、发育、环境、功能和进化联系起来，这往往阻碍了跨越不同时空尺度的生物学研究的进展，从细胞内分子的运动到生物形态的适应性变化。该项目的主要目标是开发一套广泛适用于生物形状研究的新的定量方法和工具，以满足对形状数据进行一致和可重复分析的重要需求。

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.