MPNTEXT: An Interactive Platform for Automatically Extracting Metal-Polyphenol Networks and Their Applications from Scientific Literature,Journal of Chemical Information and Modeling

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MPNTEXT: An Interactive Platform for Automatically Extracting Metal-Polyphenol Networks and Their Applications from Scientific Literature
Journal of Chemical Information and Modeling ( IF 5.6 ) Pub Date : 2024-09-11 , DOI: 10.1021/acs.jcim.4c01093
Zihui Huang ₁ , Xinyi Li ₁ , Andi Li ₁ , Yuhang Yang ₁ , Liqiang He ₁ , Zhiwen Zhang ₁ , Siwei Wu ₁ , Yang Wang ₁ , Shuting Cai ₂ , Yan He ₁ , Xujie Liu ₁

Affiliation

In recent years, metal-polyphenol networks (MPNs) have gained significant attention due to their unique properties and broad applications across various fields. However, the burgeoning volume of MPN literature necessitates the automation of chemical information extraction from the extensive corpus of unstructured data, including scientific publications. To address this challenge, we proposed a platform named MPNTEXT, which utilized natural language processing techniques and machine learning algorithms to efficiently identify and extract pertinent information, thereby assisting users in comprehending complex MPNs and their textual descriptions of applications. Users can enter keywords, such as “Fe”, “drug delivery”, or “tannic acid”, to retrieve relevant information, which is then presented in a structured format. This study aims to provide a user-friendly tool for collecting and retrieving MPN data and promotes data-driven material design. The platform offers researchers a more convenient and efficient way to design versatile MPNs and explore their applications.

中文翻译：

MPNTEXT：从科学文献中自动提取金属多酚网络及其应用的交互式平台

近年来，金属多酚网络（MPN）因其独特的性能和在各个领域的广泛应用而受到广泛关注。然而，MPN 文献数量的不断增长需要从大量非结构化数据（包括科学出版物）中自动提取化学信息。为了应对这一挑战，我们提出了一个名为 MPNTEXT 的平台，该平台利用自然语言处理技术和机器学习算法来有效识别和提取相关信息，从而帮助用户理解复杂的 MPN 及其应用程序的文本描述。用户可以输入“Fe”、“药物输送”或“单宁酸”等关键词来检索相关信息，然后以结构化格式呈现。本研究旨在提供一种用户友好的工具来收集和检索 MPN 数据，并促进数据驱动的材料设计。该平台为研究人员提供了一种更方便、更高效的方式来设计多功能 MPN 并探索其应用。

更新日期：2024-09-11

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