Development and implementation of (Q)SAR modeling within the CHARMMing web-user interface.
Development and implementation of (Q)SAR modeling within the CHARMMing web-user interface.
复制标题
在 CHARMMing Web 用户界面中开发和实施 (Q)SAR 建模。
DOI：
10.1002/jcc.23765
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发表时间：
2015
影响因子：
3
通讯作者：
Brooks,BernardR
中科院分区：
文献类型：
--
作者：
Weidlich,IwonaE;Pevzner,Yuri;Miller,BenjaminT;Filippov,IgorV;Woodcock,HLee;Brooks,BernardR
最近可公开访问的化合物及其生物活性的大型数据库（PubChem，ChEMBL）的可用性启发了我们开发基于Web的结构活性关系和定量结构活性关系建模工具，以添加到CHARMMing（www.charmming.org）提供的服务中。这个新模块实现了现代机器学习算法的一些最新进展-随机森林，支持向量机，随机梯度下降，梯度树提升等。用户可以直接从我们的界面导入Pubchem Bioassay数据集的训练数据，或者上传他或她自己的SD文件，其中包含结构和活性信息，以创建新模型（分类或数值）。然后，用户可以跟踪模型生成过程，并在新数据上运行模型以预测活动。© 2014 Wiley Periodicals，Inc.
Recent availability of large publicly accessible databases of chemical compounds and their biological activities (PubChem, ChEMBL) has inspired us to develop a web‐based tool for structure activity relationship and quantitative structure activity relationship modeling to add to the services provided by CHARMMing (www.charmming.org). This new module implements some of the most recent advances in modern machine learning algorithms—Random Forest, Support Vector Machine, Stochastic Gradient Descent, Gradient Tree Boosting, so forth. A user can import training data from Pubchem Bioassay data collections directly from our interface or upload his or her own SD files which contain structures and activity information to create new models (either categorical or numerical). A user can then track the model generation process and run models on new data to predict activity. © 2014 Wiley Periodicals, Inc.