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

eLife

Emek Demir¹  Metin Can Siper¹  Funda Durupinar²  Özgün Babur²  Augustin Luna³  Christian Dallago⁴  Chris Sander⁵  Benjamin M Gyori⁶  John A Bachman⁶  Dylan Fong⁷  John Giorgi⁷  Jeffrey V Wong⁷  Max Franz⁷  Igor Rodchenkov⁷  Gary D Bader⁸ 

[1] Computational Biology Program, Oregon Health and Science University, Portland, United States;Computer Science Department, University of Massachusetts Boston, Boston, United States;Department of Cell Biology, Harvard Medical School, Boston, United States;Department of Data Sciences, Dana-Farber Cancer Institute, Boston, United States;Broad Institute, Massachusetts Institute of Technology, Harvard University, Boston, United States;Department of Cell Biology, Harvard Medical School, Boston, United States;Department of Systems Biology, Harvard Medical School, Boston, United States;Department of Informatics, Technische Universität München, Garching, Germany;Department of Data Sciences, Dana-Farber Cancer Institute, Boston, United States;Broad Institute, Massachusetts Institute of Technology, Harvard University, Boston, United States;Laboratory of Systems Pharmacology, Harvard Medical School, Boston, United States;The Donnelly Centre, University of Toronto, Toronto, Canada;The Donnelly Centre, University of Toronto, Toronto, Canada;Department of Computer Science, Department of Molecular Genetics, University of Toronto, Toronto, United States;The Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada;Princess Margaret Cancer Centre, University Health Network, Toronto, Canada;

关键词: pathway analysis;    curation tool;    knowledge base;    science forum;    crowdsource;    None;   

DOI  :  10.7554/eLife.68292

来源: eLife Sciences Publications, Ltd

【 摘 要 】

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.

【 授权许可】

CC BY