A Fast Document Classification Algorithm for Gene Symbol Disambiguation in the BITOLA Literature-Based Discovery Support System

Gene symbol disambiguation is an important problem for biomedical text mining systems. When detecting gene symbols in MEDLINE citations one of the biggest challenges is the fact that many gene symbols also denote other, more general biomedical concepts (e.g. CT, MR). Our approach to this problem is first to classify the citations into genetic and non-genetic domains and then to detect gene symbols only in the genetic domain. We used ontological information provided by Medical Subject Headings (MeSH) for this classification task. The proposed algorithm is fast and is able to process the full MEDLINE distribution in a few hours. It achieves predictive accuracy of 0.91. The algorithm is currently implemented in the BITOLA literature-based discovery support system (http://www.mf.uni-lj.si/bitola/).

[1]  T. Tatusova,et al.  Entrez Gene: gene-centered information at NCBI , 2006, Nucleic Acids Res..

[2]  Erik M. van Mulligen,et al.  Ambiguity of Human Gene Symbols in LocusLink and MEDLINE: Creating an Inventory and a Disambiguation Test Collection , 2003, AMIA.

[3]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

[4]  Lenore K. Beitel,et al.  Underexpression of Mineralocorticoid Receptor in Colorectal Carcinomas and Association with VEGFR-2 Overexpression , 2007, Journal of Gastrointestinal Surgery.

[5]  Halil Kilicoglu,et al.  Word sense disambiguation by selecting the best semantic type based on Journal Descriptor Indexing: Preliminary experiment , 2006 .

[6]  Joyce A. Mitchell,et al.  Using literature-based discovery to identify disease candidate genes , 2005, Int. J. Medical Informatics.

[7]  Hongfang Liu,et al.  Gene name ambiguity of eukaryotic nomenclatures , 2005, Bioinform..

[8]  Saso Dzeroski,et al.  Supporting Discovery in Medicine by Association Rule Mining in Medline and UMLS , 2001, MedInfo.

[9]  Richárd Farkas,et al.  The strength of co-authorship in gene name disambiguation , 2008, BMC Bioinformatics.

[10]  George Hripcsak,et al.  Gene symbol disambiguation using knowledge-based profiles , 2007, Bioinform..

[11]  D. Swanson.  Fish Oil, Raynaud's Syndrome, and Undiscovered Public Knowledge , 2015, Perspectives in biology and medicine.

[12]  Martijn J. Schuemie,et al.  Thesaurus-based disambiguation of gene symbols , 2005, BMC Bioinformatics.

[13]  Hongfang Liu,et al.  Disambiguating Ambiguous Biomedical Terms in Biomedical Narrative Text: An Unsupervised Method , 2001, J. Biomed. Informatics.