Modeling

在第一个供资阶段，建模倡议构建了一些关系模型和生物物理模型 与细胞迁移相关的力学和分子现象，并开始发展与迁移相关 虚拟小区(VC)软件中的功能。这项活动可以被认为是 简化论议程--用数学表示法对简化的运动系统进行计算机重构 结合生物学知识和假说，并确定这些假说的后果 通过计算机生成的数值计算，使之超越人类推理。这些型号 和软件开发使令人兴奋的可能性在我们的量化 从系统生物学的角度理解细胞迁移。这些模型将从 技术观点，综合性、全面性和预见性。我们努力的一个关键特征是， 验证这样的模型并将它们用于假设预测检验工作是绝对必要的，是不是 建模是在没有实验合作者直接输入的情况下进行的。我们将在下面描述 始终如一满足这一要求的机制。 建模倡议将从长期目标出发，调查系统一级的移徙机制。 开发一种全面的细胞迁移模型。这款车型将具有模块化的特点 确定性和随机性成分。我们的方法是为每个组件开发模型 驱动细胞迁移的过程，例如， 极性的发展，突起， 粘连、收缩和后部 释放，然后将它们集成到一个 综合模型。对于其中的每一个 流程，一个“流程团队”，它包括 计算生物学家和 实验生物学家(在少数情况下， 这些功能驻留在同一 实验室)，将共同开发 一种能够捕获的“过程模型” 分子的动力学行为 特性(蛋白质水平、状态、 地点和活动)。它是通过这一点 数据将成为协作团队 制作、分析和建模 迭代地，目标是开发 来自模型预测的其他数据 并使用这些数据来改进模型。

In the first funding phase, the Modeling Initiative constructed a number of relational and biophysical models of mechanics and molecular phenomena related to cell migration and started to develop migration related capabilities within the Virtual Cell (VC) software. This activity can be considered as the last step in the reductionism agenda - in silico reconstitution of a simplified motile system using mathematical representation combining biological knowledge and hypotheses, with determination of the consequences of these hypotheses facilitated beyond human reasoning by means of computer-generated numerical calculations. These models and software development enabled the exciting possibility to make a large, critical step in our quantitative understanding of cell migration from the point of view of systems biology. The models will be standardized from the technical point of view, integrated, comprehensive and predictive. A crucial feature of our endeavor, absolutely required for validating such models and using them for hypothesis prediction-test efforts, is that no modeling is undertaken absent direct input from experimental collaborators. We will describe below the mechanism by which this requirement will be consistently met. The Modeling Initiative will investigate migration mechanisms at the systems-level with a long term goal of developing a comprehensive model of cell migration. This model will have a modular character combining deterministic and stochastic components. Our approach is to develop models for each of the component processes that drive cell migration, e.g., development of polarity, protrusion, adhesion, and contraction and rear release, and then integrate them into a comprehensive model. For each of these processes, a 'Process Team' that includes both computational biologists and experimental biologists (in a few cases, these capabilities reside within the same laboratory ), will work together to develop a 'Process Model' capable of capturing dynamic behavior in terms of molecular properties (protein levels, states, locations, and activities). It is through this collaborative team that data will be produced, analyzed, and modeled iteratively with a goal of developing additional data from model predictions and using these data to refine the models.