CORE 2: DRIVING BIOLOGICAL PROBLEMS

核心2：引发生物问题 三个驱动生物学问题将成为我们生物计算研究的焦点。大尺度DBP侧重于神经假体动力学，中尺度DBP侧重于病毒和细胞动力学，分子尺度DBP侧重于药物靶标动力学。 我们使用七个标准来选择我们的驾驶生物学问题(DBP)： 规范：问题应该是整个调查领域中的问题原型，以确保我们开发的工具具有广泛的适用性。 共同覆盖一系列尺度：中心的活动必须涵盖从分子到细胞再到生物层面的尺度，这一点至关重要。 ？以物理学为基础：DBP应该提出一个问题，可以通过表示和分析生物系统的几何和物理来解决。 数据丰富：生物学以实验数据为主。这些数据提供了驱动和验证模型和仿真的真实约束条件。 ？世界级的、敬业的实验者：我们寻求生物和计算参与者之间的紧密整合和深度互动。 ？对疾病有重要影响：我们确保我们的DBP与疾病过程或治疗相关，以确保它们有助于促进人类健康。 我们过去的DBP符合这些标准，使我们能够开发现在被非常广泛的研究人员社区使用的软件。我们接下来的三个DBP也满足这些标准，并在下面进行简要回顾。

CORE 2: DRIVING BIOLOGICAL PROBLEMS Three driving biological problems will focus our biocomputation research. A macroscale DBP focused on neuroprosthetic dynamics, a mesoscale DBP focused on viral and cellular dynamics, and a molecular scale DBP focused on drug target dynamics. We use seven criteria to select our Driving Biological Problems (DBPs): Canonical: The problem should be an archetype of problems in an entire field of inquiry to guarantee broad applicability of the tools we develop. ¿ Collectively cover a range of scales: It is critical that activities of the center cover scales from molecular through cellular to organismal levels. ¿ Physics-based: The DBP should present a problem that can be addressed by representing and analyzing the geometry and physics of the biological system. ¿ Data rich: Biology is dominated by experimental data. These data provide the real-world constraints that drive and validate models and simulations. ¿ World-class, engaged experimentalists: We seek close integration and deep interactions among the biological and computational participants. ¿ Have important implications for disease: We ensure that our DBPs are related to disease processes or treatments to ensure that they contribute to the advancement of human health. Our past DBPs met these criteria and enabled us to develop software that is now used by a very broad community of researchers. Our next three DBPs also satisfy these criteria and are briefly reviewed below.