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An approach for extracting chemical data from molecular representations

机译:从分子表示中提取化学数据的方法

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摘要

The ever-increasing quantity of chemical literature necessitates the creation of automated techniques for extracting relevant information. The digital conversion process of chemical molecule representations into their corresponding computerized illustration has been evolved using numerous applications. This work is a part of our contribution to computer-aided toxicity recognition research which predicts the possible toxic side effects of drugs on the process of drug design. The current proposed approach provides essential reviews for previous related researches in the field of automated chemical information extraction and mentions our current proposed technique that is considered as an intelligent module for converting chemical molecule structures to computerized structures. Mentioned mechanisms are used to detect bonds that are represented by letters through comparison with templates database, atoms, and lines for extracting data from graphs. A sample of 100 chemical compound structures was used to be converted into computer representation to get an overall result of 88.9% precision. Finally, a comparison between related approaches and the current proposed one at their precision rates for classification of substructure patterns was conducted.
机译:不断增加的化学文献数量需要创建用于提取相关信息的自动化技术。使用许多应用,已经演化了化学分子表示的数字转换过程在相应的计算机化插图中。这项工作是我们对计算机辅助毒性识别研究的贡献的一部分,该研究预测了药物可能在药物设计过程中可能的毒性副作用。目前的拟议方法提供了对自动化学信息提取领域之前的相关研究的基本审查,并提出了我们当前的提出技术,该技术被认为是将化学分子结构转换为计算机化结构的智能模块。提到的机制用于检测通过与模板数据库,原子和用于从图形中提取数据的线条的比较来检测由字母表示的键。使用100种化学复合结构的样品转化为计算机表示,以获得88.9%的总体精度。最后,进行了相关方法与其在其精确速率下提出的用于子结构图案分类的比较。

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