Free Text Gene Name Recognition

我们已经开始开发一个在自然语言文本中识别基因或蛋白质名称的系统。该系统目前由两个模块组成。一个是贝叶斯文本分类器，我们已经在超过50万份包含已知基因名称的文档上进行了训练。将这些文档与PubMed中的其余文本进行比较，并使用朴素贝叶斯分类器学习差异。第二个模块是Brill标记器，我们已经将其修改为在具有生物取向的文本上运行。我们采取了额外的步骤，教标签者标记由单个单词和基因标签组成的基因名称。在这方面已经学习了数百条额外的规则。在标记器之后应用几个处理步骤作为过滤器来识别多术语的基因名称等。我们目前正在评估该系统在识别测试文本集中的基因名称方面的性能。计划继续就这一制度开展工作，并将新的办法纳入基本制度，以进一步改进这一制度。

We have begun the development of a system to recognize gene or protein names in natural language text. The system currently consists of two modules. One is a Bayes text classifier that we have trained on over 500k documents that contain known gene names. These documents are compared with the remainder of the text in PubMed and the difference is learned using the naive Bayes classifier. The second module is the Brill tagger that we have modified to run on text with a biological orientation. We have taken an additional step to teach the tagger to tag gene names consisting of a single word with a GENE tag. Several hundred additional rules have been learned in this regard. Several processing steps are applied as filters after the tagger to identify gene names which are multi-term, etc. We are currently evaluating the performance of this system in recognizing gene names in a test set of text. The plan is to continue work on this system and to incorporate new approaches into the basic system to improve it further.