Frequently Asked Questions

Q: What is the purpose of this resource?

A: To provide a portal to the entire biomedical literature focussed on SARS-CoV-2, MERS-CoV and SARS-CoV. It categorises papers into a set of categories to make it easier to find relevant research and indexes by important concepts (e.g. drugs, proteins, locations, etc).

Q: How do I find papers that mention a specific therapeutic?

A: We find drug names extracted from Wikidata in papers and use a set of synonyms to extract them.

Q: What machine learning methods are used in this resource?

A: We use a deep learning (BERT-based) supervised machine learning to identify the categories of the papers. A set of papers has been annotated with relevant categories and used as training data for a system that uses the text of the title and abstract to make predictions. This is complemented with heuristics to identify specific categories, e.g. clinical trial registration numbers.

Q: Are all the papers manually curated?

A: No. A small number have been manually curated and machine learning has been used to predict the categories for all other papers

Q: Is this up-to-date?

A: Yes. The latest version of PubMed and the CORD-19 dataset are downloaded and processed every day.

Q: Can I download or export the data?

A: Yes. Each page with a table has an export button in the top right which allows you to download the table data as a CSV or JSON file. Alternatively, you can download the entire CoronaCentral dataset from Zenodo. This is regularly updated.

Q: I've found a mistake with a paper. What should I do?

A: Please flag the paper using the Flag Mistake button on the paper or use the Feedback page.

Q: Who created this resource?

A: This was created by Jake Lever, a postdoctoral researcher, supervised by Russ Altman in the Helix Group at Stanford University.

Q: How is this research funded?

A: This project has been funded through the Chan Zuckerberg Biohub and through the National Library of Medicine LM05652 grant.

Q: Where can I get more details?

A: There is now a preprint available at bioRxiv. The code for the analysis also available at

Q: How do I cite this research?

A: Please cite the preprint at bioRxiv. Below is some Bibtex if that's helpful.

@article {coronacentral,
   author = {Lever, Jake and Altman, Russ B},
   title = {Analyzing the vast coronavirus literature with {C}orona{C}entral},
   year = {2020},
   doi = {10.1101/2020.12.21.423860},
   publisher = {Cold Spring Harbor Laboratory},
   journal = {bioRxiv}

Q: Who should I contact to ask a question?

A: Please contact Jake Lever at

Q: What other projects and resources does this website rely upon?

A: This website is built using NextJS and uses the SB Admin 2 MIT-licensed Bootstrap template. This website makes use of FontAwesome assets under a Creative Commons Attribution 4.0 International license. It uses ChartJS with react-chartjs-2 to render charts. It uses React Data Table for interactive tables. It also uses Leaflet with React Leaflet to render maps from OpenStreetMap. The code for the website also available at