OpenDMAP: an open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression.
OpenDMAP: an open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression.
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OPENDMAP：开源，本体驱动的概念分析引擎，应用于捕获有关蛋白质转运，蛋白质相互作用和细胞类型特异性基因表达的知识。
DOI：
10.1186/1471-2105-9-78
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发表时间：
2008-01-31
影响因子：
3
通讯作者：
Cohen KB
中科院分区：
文献类型：
--
作者：
Hunter L;Lu Z;Firby J;Baumgartner WA Jr;Johnson HL;Ogren PV;Cohen KB
信息提取（IE）的努力被广泛认为是重要的，在利用生物医学知识的快速发展，特别是在重要的事实信息发表在不同的文献领域。在这里，我们报告的设计，实施和几个评价OpenDMAP，本体驱动的，综合概念分析系统。它通过利用本体资源中的知识，整合不同的文本处理应用程序，并使用扩展的模式语言，允许混合的句法和语义元素和变量排序，显着推进了信息提取的最新技术水平。产生OpenDMAP信息提取系统，用于提取蛋白质转运断言（transfer）、蛋白质-蛋白质相互作用断言（interaction）和基因在细胞类型中表达的断言（expression）。对每个系统进行了评估，得出的F分数范围为0.26 - 0.72（精确度0.39 - 0.85，召回率0.16 - 0.85）。此外，这些系统中的每一个都在MEDLINE中的所有摘要上运行，总共产生了72，460个传输实例，265，795个交互实例和176，153个表达实例。 OpenDMAP推进了从生物医学研究文章全文中提取蛋白质-蛋白质相互作用预测的性能标准。此外，这种性能水平似乎可以推广到其他信息提取任务，包括提取关于两个以上参数的谓词的信息。信息提取系统的输出总是从本体的元素构建的，确保知识表示是相对于精心构建的现实模型的基础。这些工作的结果可以用来提高人工策展工作的效率，并在集成多个信息提取源的系统中提供额外的功能。开源OpenDMAP代码库可在以下网址免费获得：
Information extraction (IE) efforts are widely acknowledged to be important in harnessing the rapid advance of biomedical knowledge, particularly in areas where important factual information is published in a diverse literature. Here we report on the design, implementation and several evaluations of OpenDMAP, an ontology-driven, integrated concept analysis system. It significantly advances the state of the art in information extraction by leveraging knowledge in ontological resources, integrating diverse text processing applications, and using an expanded pattern language that allows the mixing of syntactic and semantic elements and variable ordering. OpenDMAP information extraction systems were produced for extracting protein transport assertions (transport), protein-protein interaction assertions (interaction) and assertions that a gene is expressed in a cell type (expression). Evaluations were performed on each system, resulting in F-scores ranging from .26 – .72 (precision .39 – .85, recall .16 – .85). Additionally, each of these systems was run over all abstracts in MEDLINE, producing a total of 72,460 transport instances, 265,795 interaction instances and 176,153 expression instances. OpenDMAP advances the performance standards for extracting protein-protein interaction predications from the full texts of biomedical research articles. Furthermore, this level of performance appears to generalize to other information extraction tasks, including extracting information about predicates of more than two arguments. The output of the information extraction system is always constructed from elements of an ontology, ensuring that the knowledge representation is grounded with respect to a carefully constructed model of reality. The results of these efforts can be used to increase the efficiency of manual curation efforts and to provide additional features in systems that integrate multiple sources for information extraction. The open source OpenDMAP code library is freely available at
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影响因子：
3
作者：
Chen H;Sharp BM
通讯作者：
Sharp BM
影响因子：
--
作者：
Blaschke, C;Valencia, A
通讯作者：
Valencia, A
影响因子：
2.9
作者：
Blaschke, Christian;Oliveros, Juan C.;Valencia, Alfonso
通讯作者：
Valencia, Alfonso
影响因子：
5.8
作者：
Corney, DPA;Buxton, BF;Jones, DT
通讯作者：
Jones, DT
影响因子：
7.5
作者：
Bunescu, R;Ge, RF;Wong, YW
通讯作者：
Wong, YW