生物转化途径预测的进展:enviPath 的改进、数据集和新功能。

IF 7.1 2区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Journal of Cheminformatics Pub Date : 2024-08-06 DOI:10.1186/s13321-024-00881-6
Jasmin Hafner, Tim Lorsbach, Sebastian Schmidt, Liam Brydon, Katharina Dost, Kunyang Zhang, Kathrin Fenner, Jörg Wicker
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引用次数: 0

摘要

enviPath 是一个广泛使用的数据库和预测系统,主要用于预测异生物化合物的微生物生物转化途径。数据和预测系统可通过网络界面和公共 REST API 免费获取。自2016年首次发布以来,我们扩展了enviPath中的可用数据,并提高了预测系统的性能和整个系统的可用性。现在,我们提供了三个不同的数据集,涵盖了不同环境和不同实验条件下的微生物生物转化。这也使得我们能够开发出适用于更多化学物质的途径预测模型。在预测引擎中,我们针对通路预测实施了一种新的评估方法,它能更真实、更全面地反映预测结果。我们还采用了一种新颖的适用性域算法,使用户能够估计模型在其数据上的表现。最后,我们改进了实现方式,以加快整个系统的运行速度,并通过插件系统提供新的功能。科学贡献:主要科学贡献是开发了适用于多种化学品的路径预测模型、用于整体性能评估的专门评价方法以及用于用户特定性能估算的新型适用域算法。两个新数据集的引入以及欧共体类链接的创建,使 enviPath 成为微生物生物转化研究领域的独特资源。
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Advancements in biotransformation pathway prediction: enhancements, datasets, and novel functionalities in enviPath

enviPath is a widely used database and prediction system for microbial biotransformation pathways of primarily xenobiotic compounds. Data and prediction system are freely available both via a web interface and a public REST API. Since its initial release in 2016, we extended the data available in enviPath and improved the performance of the prediction system and usability of the overall system. We now provide three diverse data sets, covering microbial biotransformation in different environments and under different experimental conditions. This also enabled developing a pathway prediction model that is applicable to a more diverse set of chemicals. In the prediction engine, we implemented a new evaluation tailored towards pathway prediction, which returns a more honest and holistic view on the performance. We also implemented a novel applicability domain algorithm, which allows the user to estimate how well the model will perform on their data. Finally, we improved the implementation to speed up the overall system and provide new functionality via a plugin system.

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来源期刊
Journal of Cheminformatics
Journal of Cheminformatics CHEMISTRY, MULTIDISCIPLINARY-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
14.10
自引率
7.00%
发文量
82
审稿时长
3 months
期刊介绍: Journal of Cheminformatics is an open access journal publishing original peer-reviewed research in all aspects of cheminformatics and molecular modelling. Coverage includes, but is not limited to: chemical information systems, software and databases, and molecular modelling, chemical structure representations and their use in structure, substructure, and similarity searching of chemical substance and chemical reaction databases, computer and molecular graphics, computer-aided molecular design, expert systems, QSAR, and data mining techniques.
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