Friedman C, Kra P, Yu H, Krauthammer M, Rzhetsky A
Computer Science Dept, Queens College CUNY, Flushing, NY, 11367, USA.
Bioinformatics. 2001;17 Suppl 1:S74-82. doi: 10.1093/bioinformatics/17.suppl_1.s74.
Systems that extract structured information from natural language passages have been highly successful in specialized domains. The time is opportune for developing analogous applications for molecular biology and genomics. We present a system, GENIES, that extracts and structures information about cellular pathways from the biological literature in accordance with a knowledge model that we developed earlier. We implemented GENIES by modifying an existing medical natural language processing system, MedLEE, and performed a preliminary evaluation study. Our results demonstrate the value of the underlying techniques for the purpose of acquiring valuable knowledge from biological journals.
从自然语言段落中提取结构化信息的系统在专业领域已经取得了巨大成功。现在正是为分子生物学和基因组学开发类似应用的时机。我们展示了一个名为GENIES的系统，它根据我们之前开发的知识模型从生物学文献中提取并构建有关细胞途径的信息。我们通过修改现有的医学自然语言处理系统MedLEE来实现GENIES，并进行了初步评估研究。我们的结果证明了这些基础技术对于从生物学期刊中获取有价值知识的作用。
