MBP Scientist Develops Smart Search Application for COVID-19 Literature
Scientists all over the world have been racing to find answers since the onset of the deadly coronavirus pandemic. Seemingly overnight, a diverse array of the world’s top researchers shifted their focus to the study of Covid-19, leading to a constant stream of new pre-print articles.
Now, a Medical Biophysics scientist has developed a tool called CiteNet to help fellow researchers efficiently find, survey and review this new literature. The web-based app uses algorithms to intelligently gather literature related to Covid-19 and sort it based on defined search criteria.
“Pre-prints are completed research papers that have yet to be peer-reviewed, making them the most up-to-date,” says Bo Wang, an assistant professor in the Department of Medical Biophysics who developed the app with two students from the Vector Institute. “CiteNet indexes all the papers from the pre-print servers BioRxiv and MedRxiv, where most Covid-19 papers appear before publication.”
CiteNet is not just another search engine. It is powered by the papers themselves, rather than keywords — unlike most other academic search tools. “Using advances in natural language processing, CiteNet scans papers for semantic similarities and ranks them based on their likely relevance to the query papers,” Wang says.
CiteNet is still in the development phase, but due to the Covid-19 pandemic, Wang and his team have made the demo version of the tool available to the public. They have also created and posted a CiteNet video tutorial to illustrate how to use the app.
“We hope CiteNet will be a useful, up-to-date tool for all members of the scientific community looking to find answers in the global fight against Covid-19,” Wang says.