Pages

Sunday, March 29, 2020

Tackling SARS-CoV-2 with big data

This blog post will contain a translation I made of this short "our story" Coronavirus te lijf met big data at the MUMC+ website written by André Leblanc. The Maastricht University Medical Center+ (MUMC+) is a collaboration of our our Maastricht University Faculty of Health, Medicine, and Life Science, of which our BiGCaT research group is part.

Wikidata is a community project and I only use and contribute to it. Scholia is a project started by Finn Nielsen (Technical University of Denmark - DTU), and now has funding from the Alfred P. Sloan Foundation, coordinated by Daniel Mietchen and Lane Rasberry (University of Virginia). Further acknowledgements to Andra Waagmeester (Micelio) and Jasper Koehorst (Wageningen University) for a great collaboration on corona virus information (see also Wikidata:WikiProject_COVID-19). WikiPathways colleagues including, of course, Prof. Chris Evelo and Dr. Martina Kutmon in Maastricht, but also Dr. Alex Pico and others in San Francisco. For me it was one of the selling points of the research group when I joined in 2012.

Tackling the corona virus with big data


Scholars around the world are working relentlessly on the development of a vaccine against the new SARS-CoV-2 coronavirus. Chemist and assistant professor Egon Willighagen contributes in collaboration with colleagues at the BiGCaT Department of Bioinformatics in Maastricht to make data and knowledge easier to find for other scholars. How does that work?

Big data is the new buzz words in the scholarly community. For example, collecting worldwide data around the treatment of cancer, and extracting from the best personal, unique treatment. In the case of the new coronavirus there is a more general need to just have access to data. Since the virus outbreak in Wuhan, China, there has been an explosion of new research articles on the COVID19 and the causing SARS-CoV-2 virus. The total number of scientific publications about corona viruses itself has reached some 29 thousand. These are not only about the new virus, but also the corona viruses that roamed the world before, like SARS and MERS. Either way, this makes it practically impossible to read all these articles. Instead, access to this literature has to be provided in a different way, allowing researchers to find the knowledge and data they need for their research.

Filter
Willighagen does this by organizing scientific literature, linking information, and filtering the collection of data and publications, making it searchable for scholars. He annotates publications with search terms and author names, and uses unique, global identifiers (like personal identification numbers) to support this. This is not unlike the use of phone numbers or dictionaries.

Various tools

Wikidata is the database used by Willighagen to link the information resources, along with Scholia to visualize the results. For example, Wikidata organizes data around the new virus with the https://tools.wmflabs.org/scholia/topic/Q82069695 entry. Willighagen uses these two tools to visualize what this database knows about specific topics.

Research can take advantage of a new open access resource edited by Willighagen: https://egonw.github.io/SARS-CoV-2-Queries/. Also social media are used: Twitter is used to increase awareness and mobilize people. Willighagen: "That is from a personal motivation. I tweet articles that show important changes. Or if they emphasize aspects that show how unique and urgent the situation". And finally there is WikiPathways, a project initiated by colleagues of Willighagen, to collect even more specific knowledge about the COVID19 virus. Here's the pathway about the SARS-CoV-2 virion: https://www.wikipathways.org/index.php/Pathway:WP4846

No comments:

Post a Comment