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Wong JV, Franz M, Siper MC, et al. Author-sourced capture of pathway knowledge in computable form using Biofactoid. Elife. 2021;10doi: 10.7554/eLife.68292.
Wong, J. V., Franz, M., Siper, M. C., Fong, D., Durupinar, F., Dallago, C., Luna, A., Giorgi, J., Rodchenkov, I., Babur, �. �., Bachman, J. A., Gyori, B. M., Demir, E., Bader, G. D., & Sander, C. (2021). Author-sourced capture of pathway knowledge in computable form using Biofactoid. eLife, 10. https://doi.org/10.7554/eLife.68292
Wong, Jeffrey V, et al. "Author-sourced capture of pathway knowledge in computable form using Biofactoid." eLife vol. 10 (2021). doi: https://doi.org/10.7554/eLife.68292
Wong JV, Franz M, Siper MC, Fong D, Durupinar F, Dallago C, Luna A, Giorgi J, Rodchenkov I, Babur Ö, Bachman JA, Gyori BM, Demir E, Bader GD, Sander C. Author-sourced capture of pathway knowledge in computable form using Biofactoid. Elife. 2021 Dec 03;10. doi: 10.7554/eLife.68292. PMID: 34860157.
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Elife. 2021 Dec 03;10. doi: 10.7554/eLife.68292.

Author-sourced capture of pathway knowledge in computable form using Biofactoid.

eLife

Jeffrey V Wong, Max Franz, Metin Can Siper, Dylan Fong, Funda Durupinar, Christian Dallago, Augustin Luna, John Giorgi, Igor Rodchenkov, Özgün Babur, John A Bachman, Benjamin M Gyori, Emek Demir, Gary D Bader, Chris Sander

Affiliations

  1. The Donnelly Centre, University of Toronto, Toronto, Canada.
  2. Computational Biology Program, Oregon Health and Science University, Portland, United States.
  3. Computer Science Department, University of Massachusetts Boston, Boston, United States.
  4. Department of Cell Biology, Harvard Medical School, Boston, United States.
  5. Department of Systems Biology, Harvard Medical School, Boston, United States.
  6. Department of Informatics, Technische Universität München, Garching, Germany.
  7. Department of Data Sciences, Dana-Farber Cancer Institute, Boston, United States.
  8. Broad Institute, Massachusetts Institute of Technology, Harvard University, Boston, United States.
  9. Laboratory of Systems Pharmacology, Harvard Medical School, Boston, United States.
  10. Department of Computer Science, Department of Molecular Genetics, University of Toronto, Toronto, United States.
  11. The Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada.
  12. Princess Margaret Cancer Centre, University Health Network, Toronto, Canada.

PMID: 34860157 DOI: 10.7554/eLife.68292

Abstract

Making the knowledge contained in scientific papers machine-readable and formally computable would allow researchers to take full advantage of this information by enabling integration with other knowledge sources to support data analysis and interpretation. Here we describe Biofactoid, a web-based platform that allows scientists to specify networks of interactions between genes, their products, and chemical compounds, and then translates this information into a representation suitable for computational analysis, search and discovery. We also report the results of a pilot study to encourage the wide adoption of Biofactoid by the scientific community.

© 2021, Wong et al.

Keywords: computational biology; crowdsource; curation tool; genetics; genomics; knowledge base; none; pathway analysis; science forum; systems biology

Conflict of interest statement

JW, MF, MS, DF, FD, CD, AL, JG, IR, ÖB, JB, BG, ED, GB, CS No competing interests declared

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Grant support