Overview of BioCreative II gene normalization.
BACKGROUND
The goal of the gene normalization task is to link genes or gene products mentioned in the literature to biological databases. This is a key step in an accurate search of the biological literature. It is a challenging task, even for the human expert; genes are often described rather than referred to by gene symbol and, confusingly, one gene name may refer to different genes (often from different organisms). For BioCreative II, the task was to list the Entrez Gene identifiers for human genes or gene products mentioned in PubMed/MEDLINE abstracts. We selected abstracts associated with articles previously curated for human genes. We provided 281 expert-annotated abstracts containing 684 gene identifiers for training, and a blind test set of 262 documents containing 785 identifiers, with a gold standard created by expert annotators. Inter-annotator agreement was measured at over 90%.


RESULTS
Twenty groups submitted one to three runs each, for a total of 54 runs. Three systems achieved F-measures (balanced precision and recall) between 0.80 and 0.81. Combining the system outputs using simple voting schemes and classifiers obtained improved results; the best composite system achieved an F-measure of 0.92 with 10-fold cross-validation. A 'maximum recall' system based on the pooled responses of all participants gave a recall of 0.97 (with precision 0.23), identifying 763 out of 785 identifiers.


CONCLUSIONS
Major advances for the BioCreative II gene normalization task include broader participation (20 versus 8 teams) and a pooled system performance comparable to human experts, at over 90% agreement. These results show promise as tools to link the literature with biological databases.
Morgan
Alexander A
AA
Biomedical Informatics, Stanford University, Stanford, CA, 94305, USA.
Lu
Zhiyong
Z
Wang
Xinglong
X
Cohen
Aaron M
AM
Fluck
Juliane
J
Ruch
Patrick
P
Divoli
Anna
A
Fundel
Katrin
K
Leaman
Robert
R
Hakenberg
Jörg
J
Sun
Chengjie
C
Liu
Heng-hui
HH
Torres
Rafael
R
Krauthammer
Michael
M
Lau
William W
WW
Liu
Hongfang
H
Hsu
Chun-Nan
CN
Schuemie
Martijn
M
Cohen
K Bretonnel
KB
Hirschman
Lynette
L
D000043:Abstracting and Indexing; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D005796:Genes; D006801:Humans; D016239:MEDLINE; D039781:PubMed; D015203:Reproducibility of Results; D012958:Societies, Scientific