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

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

doi:10.7554/eLife.68292

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

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

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

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.

Original language	English (US)
Article number	e68292
Journal	eLife
Volume	10
DOIs	https://doi.org/10.7554/eLife.68292
State	Published - Dec 2021
Externally published	Yes

ASJC Scopus subject areas

General Neuroscience
General Biochemistry, Genetics and Molecular Biology
General Immunology and Microbiology

Access to Document

10.7554/eLife.68292

Cite this

@article{bebde37fa18c478a8e22983e82f948fd,

title = "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.",

author = "Wong, {Jeffrey V.} and Max Franz and Siper, {Metin Can} and Dylan Fong and Funda Durupinar and Christian Dallago and Augustin Luna and John Giorgi and Igor Rodchenkov and {\"O}zg{\"u}n Babur and Bachman, {John A.} and Gyori, {Benjamin M.} and Emek Demir and Bader, {Gary D.} and Chris Sander",

note = "Publisher Copyright: {\textcopyright} Wong et al.",

year = "2021",

month = dec,

doi = "10.7554/eLife.68292",

language = "English (US)",

volume = "10",

journal = "eLife",

issn = "2050-084X",

publisher = "eLife Sciences Publications",

}

TY - JOUR

T1 - Author-sourced capture of pathway knowledge in computable form using Biofactoid

AU - Wong, Jeffrey V.

AU - Franz, Max

AU - Siper, Metin Can

AU - Fong, Dylan

AU - Durupinar, Funda

AU - Dallago, Christian

AU - Luna, Augustin

AU - Giorgi, John

AU - Rodchenkov, Igor

AU - Babur, Özgün

AU - Bachman, John A.

AU - Gyori, Benjamin M.

AU - Demir, Emek

AU - Bader, Gary D.

AU - Sander, Chris

PY - 2021/12

Y1 - 2021/12

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85122359587&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85122359587&partnerID=8YFLogxK

U2 - 10.7554/eLife.68292

DO - 10.7554/eLife.68292

M3 - Article

C2 - 34860157

AN - SCOPUS:85122359587

SN - 2050-084X

VL - 10

JO - eLife

JF - eLife

M1 - e68292

ER -

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

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this