A literature based method for identifying gene-disease connections.
We present a statistical method that can swiftly identify, from the literature, sets of genes known to be associated with given diseases. It offers a comprehensive way to treat alias symbols, a statistical method for computing the relevance of the gene to the query, and a novel way to disambiguate gene symbols from other abbreviations. The method is illustrated by finding genes related to breast cancer.
Adamic
Lada A
LA
HP Laboratories, HP, Palo Alto, CA, 94304, USA. ladamic@hpl.hp.com
Wilkinson
Dennis
D
Huberman
Bernardo A
BA
Adar
Eytan
E
D000043:Abstracting and Indexing; D000818:Animals; D003628:Database Management Systems; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D005819:Genetic Markers / Q000235:genetics*; D020022:Genetic Predisposition to Disease / Q000145:classification / Q000235:genetics*; D005820:Genetic Testing / Q000379:methods; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D009323:Natural Language Processing; D010506:Periodicals as Topic; D018875:Vocabulary, Controlled
D005819:Genetic Markers