ChemModLab:一个基于网络的化学信息学建模实验室。

Q2 Medicine
Jacqueline M Hughes-Oliver, Atina D Brooks, William J Welch, Morteza G Khaledi, Douglas Hawkins, S Stanley Young, Kirtesh Patil, Gary W Howell, Raymond T Ng, Moody T Chu
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引用次数: 17

摘要

ChemModLab是由ECCR @ NCSU联盟在NIH支持下编写的,是一个用于拟合和评估定量结构-活性关系(QSARs)的工具箱。它的元素是:化学信息学前端,用于提供用于建模的分子描述符;一套拟合模型的方法;以及验证结果模型的方法。化合物可以作为结构输入,使用可免费获得的化学信息学前端PowerMV计算标准描述符;PowerMV还支持复合可视化。此外,用户可以直接输入自己选择的描述符,因此比较描述符的能力实际上是无限的。统计方法包括各种方法的综合集合,这些方法的有效性和效用已为该领域的专家所接受。尽可能地,这些工具是在开源软件中实现的,链接到灵活的R平台,使用户能够无缝地应用许多不同的QSAR建模方法。随着有希望的新的QSAR方法从统计和数据挖掘社区出现,它们将被纳入实验室。该网站还包含到公共领域数据集的链接,这些数据集可以用作提议的新建模方法的测试用例。ChemModLab的功能通过各种生物反应来说明,每种反应都应用了不同的建模方法。这表明在拟合的QSAR模型质量和计算要求方面存在明显差异。这个实验室是基于网络的,使用是免费的。研究人员与新的分析数据,一个新的描述符集,或新的建模方法可以很容易地建立QSAR模型和基准测试他们的结果与其他发现。用户还可以检查由QSAR模型识别的分子的多样性。此外,用户可以选择将他们的数据集放在公共区域,以促进与其他研究人员的交流;或者可以将它们隐藏起来以保护机密性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ChemModLab: a web-based cheminformatics modeling laboratory.

ChemModLab, written by the ECCR @ NCSU consortium under NIH support, is a toolbox for fitting and assessing quantitative structure-activity relationships (QSARs). Its elements are: a cheminformatic front end used to supply molecular descriptors for use in modeling; a set of methods for fitting models; and methods for validating the resulting model. Compounds may be input as structures from which standard descriptors will be calculated using the freely available cheminformatic front end PowerMV; PowerMV also supports compound visualization. In addition, the user can directly input their own choices of descriptors, so the capability for comparing descriptors is effectively unlimited. The statistical methodologies comprise a comprehensive collection of approaches whose validity and utility have been accepted by experts in the fields. As far as possible, these tools are implemented in open-source software linked into the flexible R platform, giving the user the capability of applying many different QSAR modeling methods in a seamless way. As promising new QSAR methodologies emerge from the statistical and data-mining communities, they will be incorporated in the laboratory. The web site also incorporates links to public-domain data sets that can be used as test cases for proposed new modeling methods. The capabilities of ChemModLab are illustrated using a variety of biological responses, with different modeling methodologies being applied to each. These show clear differences in quality of the fitted QSAR model, and in computational requirements. The laboratory is web-based, and use is free. Researchers with new assay data, a new descriptor set, or a new modeling method may readily build QSAR models and benchmark their results against other findings. Users may also examine the diversity of the molecules identified by a QSAR model. Moreover, users have the choice of placing their data sets in a public area to facilitate communication with other researchers; or can keep them hidden to preserve confidentiality.

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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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