title: PPInterFinder--a mining tool for extracting causal relations on human proteins from literature.
abstract: One of the most common and challenging problem in biomedical text mining is to mine protein-protein interactions (PPIs) from MEDLINE abstracts and full-text research articles because PPIs play a major role in understanding the various biological processes and the impact of proteins in diseases. We implemented, PPInterFinder--a web-based text mining tool to extract human PPIs from biomedical literature. PPInterFinder uses relation keyword co-occurrences with protein names to extract information on PPIs from MEDLINE abstracts and consists of three phases. First, it identifies the relation keyword using a parser with Tregex and a relation keyword dictionary. Next, it automatically identifies the candidate PPI pairs with a set of rules related to PPI recognition. Finally, it extracts the relations by matching the sentence with a set of 11 specific patterns based on the syntactic nature of PPI pair. We find that PPInterFinder is capable of predicting PPIs with the accuracy of 66.05% on AIMED corpus and outperforms most of the existing systems. DATABASE URL: http://www.biomining-bu.in/ppinterfinder/
authors: Data Mining and Text Mining Laboratory, Department of Bioinformatics, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India.
authors: Kalpana
authors: K
authors: Raja
authors: Suresh
authors: S
authors: Subramani
authors: Jeyakumar
authors: J
authors: Natarajan
mesh_terms: D000465:Algorithms; D057225:Data Mining / Q000379:methods*; D030562:Databases, Protein; D004493:Education; D006801:Humans; D025941:Protein Interaction Mapping; D011506:Proteins / Q000378:metabolism*; D039781:PubMed; D012984:Software; D057188:Workflow
chemical_list: D011506:Proteins