Data and text mining Discovering patterns to extract protein–protein interactions from the literature: Part II

Motivation: An enormous number of protein–protein interaction relationships are buried in millions of research articles published over the years, and the number is growing. Rediscovering them automatic-ally is a challenging bioinformatics task. Solutions to this problem also reach far beyond bioinformatics. Results: We study a new approach that involves automatically dis-covering English expression patterns, optimizing them and using them to extract protein–protein interactions. In a sister paper, we described how to generate English expression patterns related to protein–protein interactions, and this approach alone has already achieved precision and recall rates significantly higher than those of other automatic systems. This paper continues to present our theory, focusing on how to improve the patterns. A minimum description length (MDL)-based pattern-optimization algorithm is designed to reduce and merge patterns. This has significantly increased generalization power, and hence the recall and precision rates, as confirmed by our experiments