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首页> 外文期刊>Journal of chemical information and modeling >QSAR-Co: An Open Source Software for Developing Robust Multitasking or Multitarget Classification-Based QSAR Models
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QSAR-Co: An Open Source Software for Developing Robust Multitasking or Multitarget Classification-Based QSAR Models

机译:QSAR-CO:用于开发强大的多任务处理或基于多元分类的QSAR模型的开源软件

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摘要

Quantitative structure activity relationships (QSAR) modeling is a well-known computational technique with wide applications in fields such as drug design, toxicity predictions, nanomaterials, etc. However, QSAR researchers still face certain problems to develop robust classification-based QSAR models, especially while handling response data pertaining to diverse experimental and/or theoretical conditions. In the present work, we have developed an open source standalone software "QSAR-Co" (available to download at https://sites. google.com/view/qsar-co) to setup classification-based QSAR models that allow mining the response data coming from multiple conditions. The software comprises two modules: (1) the Model development module and (2) the Screen/Predict module. This user-friendly software provides several functionalities required for developing a robust multitasking or multitarget classification-based QSAR model using linear discriminant analysis or random forest techniques, with appropriate validation, following the principles set by the Organisation for Economic Co-operation and Development (OECD) for applying QSAR models in regulatory assessments.
机译:定量结构活动关系(QSAR)建模是一种着名的计算技术,具有诸如药物设计,毒性预测,纳米材料等领域的广泛应用,然而,QSAR研究人员仍然面临着开发基于稳健的QSAR模型的某些问题,特别是虽然处理与不同实验和/或理论条件有关的响应数据。在目前的工作中,我们开发了一个开源独立软件“qsar-co”(可在https://站点下载。google.com/view/qsarco)来设置基于分类的QSAR模型,允许挖掘来自多种条件的响应数据。该软件包括两个模块:(1)模型开发模块和(2)屏幕/预测模块。这种用户友好的软件提供了使用线性判别分析或随机森林技术的基于稳健的多任务或基于多元分类的QSAR模型所需的多种功能,并按照经济合作和发展组织(经合组织)规定的原则)在监管评估中应用QSAR模型。

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