A Negative Results Search Tool

Negative findings can be hard to come by in the biomedical literature. And papers reporting such findings can be darn near impossible to turn up in searches of the go-to database, PubMed. Enter University of Wisconsin, Milwaukee, biomedical informatician Hong Yu. In collaboration with her grad student Shashank Agarwal, Yu developed a search engine, called BioNOT, that can find the rare papers reporting negative findings—such as a particular gene not being associated with a particular disease—that actually get published.

BioNOT uses artificial intelligence and data mining to comb PubMed abstracts as well as open access full-text articles and papers published by Elsevier. For example, typing in "alcohol" and "heart disease" brings up a slew of excerpts from studies, highlighting results that failed to draw a link between alcohol consumption and protection against coronary heart disease.

Yu, who published a paper announcing the new technology in BMC Bioinformatics last...