ScholarlyCommons

Title

Automatically annotating documents with normalized gene lists

Author(s)

Jeremiah Crim, University of Pennsylvania
Ryan McDonald, University of Pennsylvania
Fernando Pereira, University of Pennsylvania

Date of this Version

May 2005

Document Type

Journal Article

Recommended Citation

Jeremiah Crim, Ryan McDonald, and Fernando Pereira, "Automatically annotating documents with normalized gene lists", . May 2005.

Comments

Reprinted from BMC Bioinformatics, Volume 6 (Suppl 1), Article Number S13, May 24, 2004, 7 pages.

Abstract

Background: Document gene normalization is the problem of creating a list of unique identifiers for genes that are mentioned within a document. Automating this process has many potential applications in both information extraction and database curation systems. Here we present two separate solutions to this problem. The first is primarily based on standard pattern matching and information extraction techniques. The second and more novel solution uses a statistical classifier to recognize valid gene matches from a list of known gene synonyms.

Results: We compare the results of the two systems, analyze their merits and argue that the classification based system is preferable for many reasons including performance, simplicity and robustness. Our best systems attain a balanced precision and recall in the range of 74%–92%, depending on the organism.