Planning and Workflow Management for a Virtual Laboratory for Structural Biology

我们建议创建一个基础设施，一个虚拟实验室，以支持结构生物学知识的共享，计划实验，并促进科学发现的严格过程。我们称之为虚拟实验室，因为它允许一个人坐在连接到互联网的计算机前，控制一个实验，跟踪过去由一个成熟的小组进行的实验的最相关方面，或者在关键时刻得到建议。结构生物学和其他自然科学（如物理或化学）的发现过程相当复杂，它涉及一些繁琐而耗时的活动，知识共享，结果分析，回溯。虚拟实验室将允许结构生物学家减少获得结果的时间，提高结果的质量，并通过允许科学家专注于实验和发现过程来重组人类参与。为了缩短获得结果的时间，我们需要高效的组件，完全集成的实验，仿真和建模环境，以及某种形式的知识共享和管理。为了提高解决方案的质量，我们需要将传感器完全集成到反馈回路中，并使用最佳的模型参数。最后，但并非最不重要的是，我们需要自动化简单的任务，如数据迁移，格式转换，以及为每个计算任务选择最佳运行条件。在这一领域获得高质量结果所需的高水平复杂性激励了我们的努力。基础设施的一些组成部分是结构生物学特有的，例如用于构建知识库的接口，但基本机制，例如，规划和工作流执行引擎是通用的，并且可以用于具有类似特征的其它类问题。在这项资助申请中，我们建议开发使用低温TEM方法确定三维结构的代理，并设计一个基于Petri网模型的集成工作流执行引擎，该引擎具有规划引擎和知识管理系统。我们所有的程序都是在我们的网站http://bond.cs.purdue.edu的开源许可下分发的。该项目将有助于教育和支持结构生物学实验室的知识共享。

We propose to create an infrastructure, a Virtual Laboratory, to support sharing of knowledge in structural biology, to plan an experiment, and to facilitate a rigorous process of scientific discovery. We call it a virtual laboratory because it will allow an individual sitting in front of a computer connected to the Internet, to control an experiment, to follow the most relevant aspects of an experiment conducted in the past by a well established group, or to get advice at a critical junction. The process of discovery in structural biology, and other natural sciences like physics or chemistry is fairly complex, it involves some tedious and time consuming activities, sharing of knowledge, analysis of the results, backtracking. The virtual laboratory willallow structural biologists to reduce the time to obtain the results, improve the quality of the results, and restructure the human involvement by allowing a scientist to concentrate on the experiment and the discovery process. To reduce the time to obtain results we need efficient components, fully integrated experiment, simulation, and modeling environments, and some form of knowledge sharing and management. To improve the quality of the solution we need to fully integrate sensors in the feedback loop and to use optimal model parameters. Last, but not least, we need to automate simple tasks like data migration, format conversion, and selection of optimal running condition for each computational task. The high level of sophistication necessary to obtain quality results in this field motivates our effort.Some components of the infrastructure are specific to structural biology e.g. the interfaces for building the knowledge base, but the basic mechanisms e.g., the planning and the workflow enactment engines, are general and can be used for other classes of problems with similar characteristics. In this grant application we propose to develop agents for 3D structure determination using cryo TEM methods and to design an integrated workflow enactment engine based upon a Petri Net model with a planning engine and a knowledge management system.All our programs are distributed under open source licenses from our Web site: http://bond.cs.purdue.edu. The project will contribute to education and support knowledge sharing in structural biology laboratories.