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本文引用的文献

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Public (Q)SAR Services, Integrated Modeling Environments, and Model Repositories on the Web: State of the Art and Perspectives for Future Development.网络上的公共(定量)构效关系服务、集成建模环境和模型知识库:现状与未来发展展望。
Mol Inform. 2017 Mar;36(3). doi: 10.1002/minf.201600082. Epub 2016 Oct 25.
2
BIGCHEM: Challenges and Opportunities for Big Data Analysis in Chemistry.大数据化学:化学领域大数据分析的挑战与机遇
Mol Inform. 2016 Dec;35(11-12):615-621. doi: 10.1002/minf.201600073. Epub 2016 Jul 28.
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ISIDA Property-Labelled Fragment Descriptors.ISIDA属性标记片段描述符。
Mol Inform. 2010 Dec 17;29(12):855-68. doi: 10.1002/minf.201000099. Epub 2010 Dec 9.
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Best Practices for QSAR Model Development, Validation, and Exploitation.定量构效关系(QSAR)模型开发、验证及应用的最佳实践
Mol Inform. 2010 Jul 12;29(6-7):476-88. doi: 10.1002/minf.201000061. Epub 2010 Jul 6.
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Trust, but Verify II: A Practical Guide to Chemogenomics Data Curation.《信任,但需验证II:化学基因组学数据管理实用指南》
J Chem Inf Model. 2016 Jul 25;56(7):1243-52. doi: 10.1021/acs.jcim.6b00129. Epub 2016 Jun 22.
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ZINC 15--Ligand Discovery for Everyone.锌15——面向大众的配体发现平台。
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PubChem Substance and Compound databases.美国国立医学图书馆化学物质数据库和化合物数据库。
Nucleic Acids Res. 2016 Jan 4;44(D1):D1202-13. doi: 10.1093/nar/gkv951. Epub 2015 Sep 22.
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Curation of chemogenomics data.化学基因组学数据的管理
Nat Chem Biol. 2015 Aug;11(8):535. doi: 10.1038/nchembio.1881.
9
Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds.预测化学诱导的皮肤反应。第一部分:皮肤致敏的定量构效关系模型及其在识别潜在有害化合物中的应用。
Toxicol Appl Pharmacol. 2015 Apr 15;284(2):262-72. doi: 10.1016/j.taap.2014.12.014. Epub 2015 Jan 3.
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Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization.预测化学诱导的皮肤反应。第二部分:皮肤渗透性的定量构效关系模型以及皮肤渗透性与皮肤致敏之间的关系。
Toxicol Appl Pharmacol. 2015 Apr 15;284(2):273-80. doi: 10.1016/j.taap.2014.12.013. Epub 2015 Jan 3.

化学工作台:一个可公开访问的综合化学信息学门户。

Chembench: A Publicly Accessible, Integrated Cheminformatics Portal.

作者信息

Capuzzi Stephen J, Kim Ian Sang-June, Lam Wai In, Thornton Thomas E, Muratov Eugene N, Pozefsky Diane, Tropsha Alexander

机构信息

Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, and ‡Department of Computer Science, University of North Carolina , Chapel Hill, North Carolina 27599, United States.

出版信息

J Chem Inf Model. 2017 Feb 27;57(2):105-108. doi: 10.1021/acs.jcim.6b00462. Epub 2017 Jan 19.

DOI:10.1021/acs.jcim.6b00462
PMID:28045544
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5720369/
Abstract

The enormous increase in the amount of publicly available chemical genomics data and the growing emphasis on data sharing and open science mandates that cheminformaticians also make their models publicly available for broad use by the scientific community. Chembench is one of the first publicly accessible, integrated cheminformatics Web portals. It has been extensively used by researchers from different fields for curation, visualization, analysis, and modeling of chemogenomics data. Since its launch in 2008, Chembench has been accessed more than 1 million times by more than 5000 users from a total of 98 countries. We report on the recent updates and improvements that increase the simplicity of use, computational efficiency, accuracy, and accessibility of a broad range of tools and services for computer-assisted drug design and computational toxicology available on Chembench. Chembench remains freely accessible at https://chembench.mml.unc.edu.

摘要

公开可用的化学基因组学数据量大幅增加,且对数据共享和开放科学的重视日益增强,这就要求化学信息学家也将其模型公开,以供科学界广泛使用。Chembench是首批可供公众访问的集成化学信息学网络门户之一。来自不同领域的研究人员广泛使用它来管理、可视化、分析和建模化学基因组学数据。自2008年推出以来,来自98个国家的5000多名用户对Chembench的访问量已超过100万次。我们报告了最近的更新和改进情况,这些更新和改进提高了Chembench上可用于计算机辅助药物设计和计算毒理学的各种工具和服务的易用性、计算效率、准确性和可访问性。Chembench仍可通过https://chembench.mml.unc.edu免费访问。