In a study published today in the open access journal Journal of Biology, researchers manually curated the entire literature for genetic and physical protein interactions in the yeast Saccharomyces cerevisiae, an important model system for human cells. The database enabled better predictions of gene functions and protein interactions than all previous data collections combined.
Mike Tyers from the Samuel Lunenfeld Research Institute of Mount Sinai Hospital in Toronto, Canada and colleagues from other institutions in Canada and the USA, read over 30,000 publications on S. cerevisiae and recorded over 22,000 protein interactions and over 11,000 genetic interactions. Surprisingly, Tyers and colleagues found less than 20% overlap between their literature dataset and the datasets generated using high-throughput methods for interaction detection, indicating that many more interactions are likely to be discovered.
Tyers and colleagues’ database will enable researchers to gain further insight into individual gene functions and biological network features in yeast, and by extension other species including humans. Their study also shows that it is possible to search and sort a large amount of existing knowledge from the literature within a relatively short time frame. This approach could be applied to other organisms, from E. Coli to humans.
The literature interaction dataset is publicly available at the BioGRID database (http://thebiogrid.org/) and at the Saccharomyces Genome Database (http://www.yeastgenome.org/).
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