2008 AGraphKernelForPPIExtraction

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Subject Headings: Protein-Protein Interaction Extraction Task, Supervised Graph Kernel Algorithm.

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Abstract

In this paper, we propose a graph kernel based approach for the automated extraction of protein-protein interactions (PPI) from scientific literature. In contrast to earlier approaches to PPI extraction, the introduced all dependency-paths kernel has the capability to consider full, general dependency graphs. We evaluate the proposed method across five publicly available PPI corpora providing the most comprehensive evaluation done for a machine learning based PPI-extraction system.

Our method is shown to achieve state-of-the-art performance with respect to comparable evaluations, achieving 56.4 F-score and 84.8 AUC on the AImed corpus. Further, we identify several pitfalls that can make evaluations of PPI-extraction systems incomparable, or even invalid. These include incorrect cross-validation strategies and problems related to comparing F-score results achieved on different evaluation resources.


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2008 AGraphKernelForPPIExtractionAntti Airola
Sampo Pyysalo
Jari Björne
Tapio Pahikkala
Filip Ginter
Tapio Salakoski
A Graph Kernel for Protein-Protein Interaction Extractionhttp://aclweb.org/anthology-new/W/W08/W08-0601.pdf2008