Coulet Adrien, Shah Nigam, Hunter Lawrence, Barral Chitta, Altman Russ B
Department of Genetics, Stanford University, Stanford, CA 94305, USA.
Pac Symp Biocomput. 2010:485-7. doi: 10.1142/9789814295291_0051.
Advances in concept recognition and natural language parsing have led to the development of various tools that enable the identification of biomedical entities and relationships between them in text. The aim of the Genotype-Phenotype-Drug Relationship Extraction from Text workshop (or GPD-Rx workshop) is to examine the current state of art and discuss the next steps for making the extraction of relationships between biomedical entities integral to the curation and knowledge management workflow in Pharmacogenomics. The workshop will focus particularly on the extraction of Genotype-Phenotype, Genotype-Drug, and Phenotype-Drug relationships that are of interest to Pharmacogenomics. Extracting and structuring such text-mined relationships is a key to support the evaluation and the validation of multiple hypotheses that emerge from high throughput translational studies spanning multiple measurement modalities. In order to advance this agenda, it is essential that existing relationship extraction methods be compared to one another and that a community wide benchmark corpus emerges; against which future methods can be compared. The workshop aims to bring together researchers working on the automatic or semi-automatic extraction of relationships between biomedical entities from research literature in order to identify the key groups interested in creating such a benchmark.
概念识别和自然语言解析方面的进展催生了各种工具，这些工具能够识别文本中的生物医学实体及其之间的关系。文本基因型-表型-药物关系提取研讨会（或GPD-Rx研讨会）的目的是审视当前的技术水平，并讨论使生物医学实体之间关系的提取成为药物基因组学中策展和知识管理工作流程不可或缺部分的后续步骤。该研讨会将特别关注药物基因组学感兴趣的基因型-表型、基因型-药物和表型-药物关系的提取。提取并构建此类文本挖掘关系是支持对来自跨越多种测量方式的高通量转化研究中出现的多个假设进行评估和验证的关键。为了推进这一议程，必须将现有的关系提取方法相互比较，并形成一个全社区范围的基准语料库，以便未来的方法能够与之进行比较。该研讨会旨在汇聚致力于从研究文献中自动或半自动提取生物医学实体之间关系的研究人员，以确定对创建这样一个基准感兴趣的关键群体。
