实现QPhAR算法的一组新的KNIME节点。

IF 2.8 4区 医学 Q3 CHEMISTRY, MEDICINAL
Stefan Kohlbacher, Gökhan Ibis, Christian Permann, Sharon Bryant, Thierry Langer, Thomas Seidel
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引用次数: 0

摘要

新研究方法的传播,特别是化学信息学软件的传播,在很大程度上取决于它们对只有很少或没有编程技能和计算机科学知识的非专业用户的适用性。在过去的几年中,可视化编程已经变得非常流行,它也使没有深入编程技能的研究人员能够使用预定义的标准过程存储库中的元素开发定制的数据处理管道。在这项工作中,我们提出了一组实现QPhAR算法的KNIME平台节点的开发。我们将展示如何将开发的KNIME节点包含在用于生物活性预测的典型工作流程中。此外,我们提出了获得高质量QPhAR模型应该遵循的最佳实践指南。最后,我们展示了一个典型的工作流来训练和优化KNIME中的QPhAR模型,用于一组给定的输入化合物,应用所讨论的最佳实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A new set of KNIME nodes implementing the QPhAR algorithm.

A new set of KNIME nodes implementing the QPhAR algorithm.

Dissemination of novel research methods, especially in the form of chemoinformatics software, depends heavily on their ease of applicability for non-expert users with only a little or no programming skills and knowledge in computer science. Visual programming has become widely popular over the last few years, also enabling researchers without in-depth programming skills to develop tailored data processing pipelines using elements from a repository of predefined standard procedures. In this work, we present the development of a set of nodes for the KNIME platform implementing the QPhAR algorithm. We show how the developed KNIME nodes can be included in a typical workflow for biological activity prediction. Furthermore, we present best-practice guidelines that should be followed to obtain high-quality QPhAR models. Finally, we show a typical workflow to train and optimise a QPhAR model in KNIME for a set of given input compounds, applying the discussed best practices.

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来源期刊
Molecular Informatics
Molecular Informatics CHEMISTRY, MEDICINAL-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.30
自引率
2.80%
发文量
70
审稿时长
3 months
期刊介绍: Molecular Informatics is a peer-reviewed, international forum for publication of high-quality, interdisciplinary research on all molecular aspects of bio/cheminformatics and computer-assisted molecular design. Molecular Informatics succeeded QSAR & Combinatorial Science in 2010. Molecular Informatics presents methodological innovations that will lead to a deeper understanding of ligand-receptor interactions, macromolecular complexes, molecular networks, design concepts and processes that demonstrate how ideas and design concepts lead to molecules with a desired structure or function, preferably including experimental validation. The journal''s scope includes but is not limited to the fields of drug discovery and chemical biology, protein and nucleic acid engineering and design, the design of nanomolecular structures, strategies for modeling of macromolecular assemblies, molecular networks and systems, pharmaco- and chemogenomics, computer-assisted screening strategies, as well as novel technologies for the de novo design of biologically active molecules. As a unique feature Molecular Informatics publishes so-called "Methods Corner" review-type articles which feature important technological concepts and advances within the scope of the journal.
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