BioAssay ontology annotations facilitate cross-analysis of diverse high-throughput screening data sets.
BioAssay ontology annotations facilitate cross-analysis of diverse high-throughput screening data sets.
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DOI：
10.1177/1087057111400191
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发表时间：
2011-04
影响因子：
--
通讯作者：
Lemmon V
中科院分区：
文献类型：
--
作者：
Schürer SC;Vempati U;Smith R;Southern M;Lemmon V
高通量筛选数据库，如PubChem，代表了开发小分子化学探针的宝贵资源，可以作为药物发现计划的切入点。虽然PubChem提供的松散数据格式具有很大的灵活性，但重要的注释（如所采用的分析格式和技术）并未明确索引。我们之前已经开发了一个BioAssay Ontology（BAO），并使用标准化的BAO术语管理了350多个检测。在这里，我们描述了使用BAO注释来分析大量采用基于荧光素酶和β-内酰胺酶的技术的测定。我们确定了混杂的化学型属于不同的子类别的测定和特定的机制，这些化学型干扰报告基因测定。我们的研究结果表明，PubChem中的数据可用于识别非特异性干扰特定技术的混杂化合物。此外，我们表明，BAO是一个有价值的工具集，用于识别相关检测和系统生成超出单个检测或筛选活动范围的见解。
High-throughput screening data repositories, such as PubChem, represent valuable resources for the development of small molecule chemical probes and can serve as entry points for drug discovery programs. While the loose data format offered by PubChem allows for great flexibility, important annotations, such as the assay format and technologies employed, are not explicitly indexed. We have previously developed a BioAssay Ontology (BAO) and curated over 350 assays with standardized BAO terms. Here we describe the use of BAO annotations to analyze a large set of assays that employ luciferase- and β-lactamase-based technologies. We identified promiscuous chemotypes pertaining to different sub-categories of assays and specific mechanisms by which these chemotypes interfere in reporter gene assays. Our results show that the data in PubChem can be used to identify promiscuous compounds that interfere non-specifically with particular technologies. Furthermore, we show that BAO is a valuable toolset for the identification of related assays and for the systematic generation of insights that are beyond the scope of individual assays or screening campaigns.
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影响因子：
10.4
作者：
Xia M;Huang R;Witt KL;Southall N;Fostel J;Cho MH;Jadhav A;Smith CS;Inglese J;Portier CJ;Tice RR;Austin CP
通讯作者：
Austin CP
影响因子：
7.3
作者：
Babaoglu, Kerim;Simeonov, Anton;Shoichet, Brian K.
通讯作者：
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14.9
作者：
Wang Y;Bolton E;Dracheva S;Karapetyan K;Shoemaker BA;Suzek TO;Wang J;Xiao J;Zhang J;Bryant SH
通讯作者：
Bryant SH
影响因子：
56.9
作者：
Zlokarnik, G;Negulescu, PA;Tsien, RY
通讯作者：
Tsien, RY
影响因子：
5.6
作者：
Rogers, David;Hahn, Mathew
通讯作者：
Hahn, Mathew