title: Extracting human protein interactions from MEDLINE using a full-sentence parser.
abstract: BACKGROUND
  The living cell is a complex machine that depends on the proper functioning of its numerous parts, including proteins. Understanding protein functions and how they modify and regulate each other is the next great challenge for life-sciences researchers. The collective knowledge about protein functions and pathways is scattered throughout numerous publications in scientific journals. Bringing the relevant information together becomes a bottleneck in a research and discovery process. The volume of such information grows exponentially, which renders manual curation impractical. As a viable alternative, automated literature processing tools could be employed to extract and organize biological data into a knowledge base, making it amenable to computational analysis and data mining.
  
  
  RESULTS
  We present MedScan, a completely automated natural language processing-based information extraction system. We have used MedScan to extract 2976 interactions between human proteins from MEDLINE abstracts dated after 1988. The precision of the extracted information was found to be 91%. Comparison with the existing protein interaction databases BIND and DIP revealed that 96% of extracted information is novel. The recall rate of MedScan was found to be 21%. Additional experiments with MedScan suggest that MEDLINE is a unique source of diverse protein function information, which can be extracted in a completely automated way with a reasonably high precision. Further directions of the MedScan technology improvement are discussed.
  
  
  BACKGROUND
  MedScan is available for commercial licensing from Ariadne Genomics, Inc.
authors.affiliation: Ariadne Genomics, Inc., 9700 Great Seneca Hwy, Rockville, MD 20850, USA. nikolai@ariadnegenomics.com
authors.forename: Nikolai
authors.initials: N
authors.lastname: Daraselia
authors.forename: Anton
authors.initials: A
authors.lastname: Yuryev
authors.forename: Sergei
authors.initials: S
authors.lastname: Egorov
authors.forename: Svetalana
authors.initials: S
authors.lastname: Novichkova
authors.forename: Alexander
authors.initials: A
authors.lastname: Nikitin
authors.forename: Ilya
authors.initials: I
authors.lastname: Mazo
mesh_terms: D000043:Abstracting and Indexing; D001185:Artificial Intelligence; D003628:Database Management Systems; D030562:Databases, Protein; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D016239:MEDLINE; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated; D010506:Periodicals as Topic; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000378:metabolism*; D015203:Reproducibility of Results; D012660:Semantics; D012680:Sensitivity and Specificity; D018875:Vocabulary, Controlled
chemical_list: D011506:Proteins