Bioinformatics Advance Access originally published online on January 22, 2004
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Bioinformatics 20(5) © Oxford University Press 2004; all rights reserved.
Extracting human protein interactions from MEDLINE using a full-sentence parser
Ariadne Genomics, Inc., 9700 Great Seneca Hwy, Rockville, MD 20850, USA
Received on July 22, 2003
; revised on September 29, 2003
; accepted on October 3, 2003
Advance Access Publication January 22, 2004
Motivation: 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.
Availability: MedScan is available for commercial licensing from Ariadne Genomics, Inc.
Contact: nikolai{at}ariadnegenomics.com
* To whom correspondence should be addressed.
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  H. Liu, Z.-Z. Hu, M. Torii, C. Wu, and C. Friedman Quantitative Assessment of Dictionary-based Protein Named Entity Tagging J. Am. Med. Inform. Assoc., September 1, 2006; 13(5): 497 - 507. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P. K. Shah and P. Bork LSAT: learning about alternative transcripts in MEDLINE Bioinformatics, April 1, 2006; 22(7): 857 - 865. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 I. Ispolatov, A. Yuryev, I. Mazo, and S. Maslov Binding properties and evolution of homodimers in protein-protein interaction networks Nucleic Acids Res., June 27, 2005; 33(11): 3629 - 3635. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. Santos, D. Eggle, and David. J. States Wnt pathway curation using automated natural language processing: combining statistical methods with partial and full parse for knowledge extraction Bioinformatics, April 15, 2005; 21(8): 1653 - 1658. [Abstract] [Full Text] [PDF]
|
|