科学工作流程推理

Z. Lacroix, C. Legendre, S. Tüzmen
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引用次数: 15

摘要

科学工作流程描述了从实验设计、数据捕获、集成、处理和分析到科学发现的科学过程。实验室信息管理系统(LIMS)协调湿实验室任务、样品和仪器的管理,并允许对类似业务的参数进行推理,例如订购(例如,发票)和组织(自动化和优化),而工作流系统支持工作流程的芯片设计以执行。我们提出了一种支持对混合湿任务和数字任务的科学工作流进行推理的方法。实际上,为了预测结果的质量或确定适合预期结果的参数,通常首先用数字资源设计和模拟实验。ProtocolDB允许设计可以结合湿任务和数字任务的科学工作流,并提供关于性能、质量和成本的预测和推理框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reasoning on Scientific Workflows
Scientific workflows describe the scientific process from experimental design, data capture, integration, processing, and analysis that leads to scientific discovery. Laboratory Information Management Systems (LIMS) coordinate the management of wet lab tasks, samples, and instruments and allow reasoning on business-like parameters such as ordering (e.g., invoicing) and organization (automation and optimization) whereas workflow systems support the design of workflows in-silico for their execution. We present an approach that supports reasoning on scientific workflows that mix wet and digital tasks. Indeed, experiments are often first designed and simulated with digital resources in order to predict the quality of the result or to identify the parameters suitable for the expected outcome. ProtocolDB allows the design of scientific workflows that may combine wet and digital tasks and provides the framework for prediction and reasoning on performance, quality, and cost.
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