Signaling network reconstruction from biosensor image fluctuations

描述（由申请人提供）：大多数人类疾病和病症可被视为细胞组分被破坏的投射。这种异常抑制和/或修改细胞过程之间的自然信息流，损害适当的细胞决策。例如，小GT3蛋白的突变可导致异常细胞迁移。这种对异常过程的简单描述突出了不仅要探测信息是如何传递的重要性，例如通过氨基酸磷酸化，还要探测它从给定点开始的方向。这种方向性的发现潜在地定义了给定细胞成分的功能。例如，蛋白质的活性形式在细胞的特定区域开启特定的细胞行为。生物传感器技术已被提出来克服目前经典生物化学方法在建立信号通路功能过程中的局限性。这些荧光结构允许测量活细胞中所研究分子的定位和活性状态。由于蛋白质可以在不同的细胞位置与不同的分子相互作用，生物传感器技术作为一种强大的工具，可以解决给定蛋白质在时间和空间上的不同调节问题。该建议侧重于生物传感器成像数据的计算分析。主要目标是建立一套计算工具，从生物传感器图像中推断分子之间的路径和特定的细胞行为。作为概念验证，该项目的第二部分重点是使用以下方法阐明Rac 1在细胞板状伪足区域的调节： 提出的计算工具。这一挑战建立了这里提出的计算工具的适用性和相关性。

DESCRIPTION (provided by applicant): Most human diseases and disorders can be seen as a projection of disrupted cellular components. Such anomalies restrain and/or modify the natural flow of information among the cellular processes, impairing appropriate cell decision. For instance, mutation of the small GTPase proteins can lead to abnormal cell migration. This simplistic description of an aberrant process highlights the importance of probing not only how information is transmitted, e.g. through amino acid phosphorylation, but also the direction it takes from a given point. The discovery of this directionality potentially defines the function of given cellular component. For example, an active form of a protein switches on a specific cellular behavior at a particular region of the cell. Biosensor technology has been proposed to overcome the current limitations of classical biochemical methods on the process of establishing signaling pathway functionality. These fluorescent constructs allow the measurement of the localization and the active state of the studied molecule in living cells. Because proteins can interact with different molecules in different cellular locations, biosensor technology stands out as a powerful tool to address questions of how differently regulated a given protein is in time and space. This proposal focuses on the computational analysis of biosensor imaging data. The main goal is to build a set of computational tools that will infer paths among molecules and specific cellular behavior from biosensor images. As a proof of concept, the second part of this project focuses on the elucidation of Rac1 regulation at the lamellipodia region of cells using the proposed computational tools. This challenge sets up the suitability and relevance of the computational tools proposed here.