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PPI extraction through biological literature curation has been widely employed for proteome analysis. There is a strong need for a tool that can assist researchers in extracting comprehensive PPI information through literature curation, which is critical in research on protein, e.g., construction of protein interaction network, identification of protein signaling pathway and discovery of meaningful protein interaction. However, most of current tools can only extract PPI relations. None of them are capable of extracting other important PPI information, such as interaction directions, effects and functional annotations. To address these issues, this paper proposes PPICurator, a novel tool for extracting comprehensive PPI information with a variety of logic and syntax features based on a new support vector machine (SVM) classifier. PPICurator provides a friendly web-based user interface. It is a platform that automates the extraction of comprehensive PPI information through literature, including PPI relations, as well as their confidential scores, interaction directions, effects and functional annotations. Thus, PPICurator is more comprehensive than state-of-the-art tools. Moreover, it outperforms state-of-the-art tools in the accuracy of PPI relation extraction measured by F-score and recall on the widely-used open datasets. PPICurator is available at https://ppicurator.hupo.org.cn. This article is protected by copyright. All rights reserved.
This article was published in the following journal.
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Methods for determining interaction between proteins.
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