Author-sourced capture of pathway knowledge in computable form using Biofactoid
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 03, 2021
- Source ID
- 10.7554/elife.68292
Entities
People
- Augustin Luna
- Benjamin M Gyori
- Chris Sander
- Christian Dallago
- Dylan Fong
- Emek Demir
- Funda Durupinar
- Gary D. Bader
- Igor Rodchenkov
- Jeffrey V Wong
- John Bachman
- John Giorgi
- Max Franz
- Metin Can Siper
- Ozgun Babur
Organizations
- Dana–Farber Cancer Institute
- Defense Advanced Research Projects Agency
- Harvard Medical School
- Massachusetts Institute of Technology
- Mount Sinai Hospital
- National Human Genome Research Institute
- National Institute of General Medical Sciences
- Oregon Health & Science University
- Princess Margaret Cancer Centre
- Technical University of Munich
- University of Massachusetts Boston
- University of Toronto