Laboratory of Organic and Macromolecular Chemistry (IOMC), Friedrich Schiller University Jena, Humboldstr. 10, 07743 Jena, Germany; Jena Center for Soft Matter (JCSM), Friedrich Schiller University Jena, Philosophenweg 7, 07743 Jena, Germany.
Laboratory of Organic and Macromolecular Chemistry (IOMC), Friedrich Schiller University Jena, Humboldstr. 10, 07743 Jena, Germany; Jena Center for Soft Matter (JCSM), Friedrich Schiller University Jena, Philosophenweg 7, 07743 Jena, Germany.
STAR Protoc. 2024 Jun 21;5(2):103055. doi: 10.1016/j.xpro.2024.103055. Epub 2024 May 2.
To supply chemical structures of polymers for machine learning applications, decoding is necessary. Here, we present a protocol for generating polymer fingerprints (PFPs), which are representations of molecular structures, using a polymer-specific decoder. We outline steps for downloading, installing, and basic application of the software. Moreover, we present procedures for processing and analyzing polymer structure data and the preparation for integration into machine learning methods. On this basis, we explain how artificial neural networks can be utilized to predict polymer properties. For complete details on the use and execution of this protocol, please refer to Köster et al..
为了在机器学习应用中提供聚合物的化学结构，需要进行解码。在这里，我们提出了一种使用聚合物特定解码器生成聚合物指纹（PFPs）的方案，PFPs 是分子结构的表示形式。我们概述了下载、安装和软件基本应用的步骤。此外，我们还介绍了处理和分析聚合物结构数据以及准备将其集成到机器学习方法中的步骤。在此基础上，我们解释了如何利用人工神经网络来预测聚合物性能。有关此方案使用和执行的完整详细信息，请参阅 Köster 等人的研究。
