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Capturing scientific knowledge in computable form

View ORCID ProfileJeffrey V. Wong, View ORCID ProfileMax Franz, Metin Can Siper, Dylan Fong, Funda Durupinar, View ORCID ProfileChristian Dallago, View ORCID ProfileAugustin Luna, View ORCID ProfileJohn Giorgi, Igor Rodchenkov, View ORCID ProfileÖzgün Babur, View ORCID ProfileJohn A. Bachman, View ORCID ProfileBenjamin M. Gyori, View ORCID ProfileEmek Demir, View ORCID ProfileGary D. Bader, View ORCID ProfileChris Sander
doi: https://doi.org/10.1101/2021.03.10.382333
Jeffrey V. Wong
1The Donnelly Centre, University of Toronto, Toronto, Ontario, M5S 3E1, Canada
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Max Franz
1The Donnelly Centre, University of Toronto, Toronto, Ontario, M5S 3E1, Canada
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Metin Can Siper
2Computational Biology Program, Oregon Health and Science University, Portland, OR 97239, USA
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Dylan Fong
1The Donnelly Centre, University of Toronto, Toronto, Ontario, M5S 3E1, Canada
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Funda Durupinar
3Computer Science Department, University of Massachusetts Boston, 100 Morrissey Boulevard Boston, MA 02125
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Christian Dallago
5Department of Cell Biology, Harvard Medical School, Boston, MA, 02215, USA
6Department of Systems Biology, Harvard Medical School, Boston, MA, 02215, USA
7Department of Informatics, Technische Universität München, 85748 Garching, Germany
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Augustin Luna
4Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
5Department of Cell Biology, Harvard Medical School, Boston, MA, 02215, USA
8Broad Institute of MIT and Harvard, Boston, MA, 02142, USA
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John Giorgi
1The Donnelly Centre, University of Toronto, Toronto, Ontario, M5S 3E1, Canada
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Igor Rodchenkov
1The Donnelly Centre, University of Toronto, Toronto, Ontario, M5S 3E1, Canada
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Özgün Babur
3Computer Science Department, University of Massachusetts Boston, 100 Morrissey Boulevard Boston, MA 02125
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John A. Bachman
9Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, 02115, USA
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Benjamin M. Gyori
9Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, 02115, USA
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Emek Demir
2Computational Biology Program, Oregon Health and Science University, Portland, OR 97239, USA
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Gary D. Bader
1The Donnelly Centre, University of Toronto, Toronto, Ontario, M5S 3E1, Canada
10Department of Computer Science, University of Toronto, Ontario, M5S 2E4, Canada
11Department of Molecular Genetics, University of Toronto, Ontario, M5S 1A8, Canada
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Chris Sander
4Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
5Department of Cell Biology, Harvard Medical School, Boston, MA, 02215, USA
8Broad Institute of MIT and Harvard, Boston, MA, 02142, USA
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ABSTRACT

Technological advances in computing provide major opportunities to accelerate scientific discovery. The wide availability of structured knowledge would allow us to take full advantage of these by enabling efficient human-computer interaction. Traditionally, biological knowledge is captured in publications and knowledge bases, however, the information in articles is not directly accessible to computers, and knowledge bases are constrained by finite resources available for manual curation. To accelerate knowledge capture and communication and to keep pace with the rapid growth of scientific reports, we developed the Biofactoid (biofactoid.org) software suite, which crowdsources structured knowledge in articles from authors. Biofactoid is a web-based system that lets scientists draw a network of interactions between genes, their products, and chemical compounds and employs smart-automation to translate user input into a structured language using the expressive power of a formal ontology. The resulting data is shared via public information resources, enabling author-curated knowledge to be appreciated in the context of all existing computable knowledge. Authors of recently published papers across a range of journals have already contributed their pathway information, much of which is novel and extends existing pathway databases into new biological areas. We envision the adoption of Biofactoid for crowdsourced curation by scientists and publishers as part of an ecosystem of tools that accelerate scientific communication and discovery.

Availability Biofactoid server at https://biofactoid.org

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted March 11, 2021.
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Capturing scientific knowledge in computable form
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
bioRxiv 2021.03.10.382333; doi: https://doi.org/10.1101/2021.03.10.382333
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Capturing scientific knowledge in computable form
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
bioRxiv 2021.03.10.382333; doi: https://doi.org/10.1101/2021.03.10.382333

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