Integrating Semantic Information into Multiple Kernels for Protein-Protein Interaction Extraction from Biomedical Literatures

• Published in: PloS one Vol. 9; no. 3; p. e91898
• Main Authors: Li, Lishuang, Zhang, Panpan, Zheng, Tianfu, Zhang, Hongying, Jiang, Zhenchao, Huang, Degen
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 12.03.2014; Public Library of Science (PLoS)
• Subjects: Algorithms; Artificial intelligence; Automation; Bioinformatics; Biology; Biomedical Research; Computer Science; Feature extraction; Information retrieval; Kernels; Keywords; Learning algorithms; Linguistics; Machine learning; Medical research; Medical Subject Headings; Natural language; Natural Language Processing; Ontology; Protein interaction; Protein Interaction Mapping; Protein-protein interactions; Proteins; Semantics; Shortest-path problems; Similarity; Studies; Support vector machines; Teaching methods; Trees

Protein-Protein Interaction (PPI) extraction is an important task in the biomedical information extraction. Presently, many machine learning methods for PPI extraction have achieved promising results. However, the performance is still not satisfactory. One reason is that the semantic resources were...