Dataset Associated with the Manuscript "Path Toward High-Throughput Synthesis Planning via Performance Benchmarking"

In the frame of the chemistry automation program of the NCATS/NIH, called "ASPIRE", we developed an evidence-based computer aided synthesis planning (CASP) platform that is built on a central reaction knowledge graph. With the help of the ASPIRE Integrated Computational Platform's Application Programming Interface (AICP API) it is possible to identify synthesis routes for robotic platforms in an autonomous manner. The goal of the study associated with the enclosed dataset was to achieve a level of performance in terms of synthesis route identification that facilitates autonomous chemical synthesis in a high-throughput setting. A combination of network theoretical and data engineering approaches led to a breakthrough, which enabled us to realize the aim of the study.Here we include the input dataset as well as output files generated during the various analyses of the study.

在NCATS/NIH的化学自动化项目框架内，即所谓的‘ASPIRE’项目中，我们开发了一个基于中心反应知识图谱的证据驱动计算机辅助合成规划（CASP）平台。借助ASPIRE集成计算平台的应用程序编程接口（AICP API），能够以自主方式识别适用于机器人平台的合成路径。与所附数据集相关的研究目标是在合成路径识别方面达到一个水平，从而在高通量设置中促进自主化学合成。网络理论方法与数据工程技术的结合取得突破，使我们实现了研究目标。在此，我们包括输入数据集以及研究分析过程中生成的输出文件。