Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, USA.
Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA.
Beilstein J Nanotechnol. 2015 Jul 1;6:1439-49. doi: 10.3762/bjnano.6.149. eCollection 2015.
Literature in the field of nanotechnology is exponentially increasing with more and more engineered nanomaterials being created, characterized, and tested for performance and safety. With the deluge of published data, there is a need for natural language processing approaches to semi-automate the cataloguing of engineered nanomaterials and their associated physico-chemical properties, performance, exposure scenarios, and biological effects. In this paper, we review the different informatics methods that have been applied to patent mining, nanomaterial/device characterization, nanomedicine, and environmental risk assessment. Nine natural language processing (NLP)-based tools were identified: NanoPort, NanoMapper, TechPerceptor, a Text Mining Framework, a Nanodevice Analyzer, a Clinical Trial Document Classifier, Nanotoxicity Searcher, NanoSifter, and NEIMiner. We conclude with recommendations for sharing NLP-related tools through online repositories to broaden participation in nanoinformatics.
随着越来越多的工程纳米材料被制造、表征和测试其性能和安全性，纳米技术领域的文献呈指数级增长。随着已发表数据的大量涌现，需要采用自然语言处理方法来半自动地对工程纳米材料及其相关物理化学特性、性能、暴露情况和生物效应进行编目。在本文中，我们回顾了已应用于专利挖掘、纳米材料/器件表征、纳米医学和环境风险评估的不同信息学方法。确定了九种基于自然语言处理 (NLP) 的工具：NanoPort、NanoMapper、TechPerceptor、文本挖掘框架、纳米器件分析器、临床试验文档分类器、纳米毒性搜索器、NanoSifter 和 NEIMiner。我们最后提出了通过在线存储库共享 NLP 相关工具的建议，以扩大纳米信息学的参与度。
