Modeling

在第一个供资阶段，建模倡议建立了一些关系和生物物理模型， 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的 虚拟小区（VC）软件中的功能。这项活动可以被认为是最后一步， 还原论议程-使用数学表示的简化运动系统的计算机重构 结合生物学知识和假设，确定这些假设的后果 通过计算机生成的数值计算，超越了人类的推理。这些模型 和软件开发使我们能够在定量方面迈出重要的一步， 从系统生物学的角度理解细胞迁移。这些模型将标准化， 从技术的角度，综合性、全面性和预测性。我们奋进的一个关键特征， 验证这些模型并将其用于假设预测检验工作绝对需要的是， 在没有来自实验合作者的直接输入的情况下进行建模。我们将在下面描述 这一要求将始终得到满足的机制。 建模计划将以长期目标研究系统级的迁移机制 开发一个全面的细胞迁移模型。这种模式将有一个模块化的字符组合 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， 附着力、收缩力和后移力 释放，然后将它们集成到一个 综合模型为每个这些 流程，一个“流程团队”，包括 计算生物学家和 实验生物学家（在少数情况下， 这些能力存在于同一个 实验室），将共同努力， 一个“过程模型”，能够捕获 分子动力学行为 属性（蛋白质水平，状态， 位置和活动）。正是通过这种 协作团队，数据将 生产、分析和建模 不断迭代， 来自模型预测的额外数据 并利用这些数据来完善模型。

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.