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Updated: Apr 27, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways

A Web Tool for Generating High Quality Machine-readable Biological Pathways

Published on: February 8, 2017

Processing biological literature with customizable Web services supporting interoperable formats.

Rafal Rak¹, Riza Theresa Batista-Navarro², Jacob Carter³

¹National Centre for Text Mining, School of Computer Science, University of Manchester, M1 7DN, UK and Department of Computer Science, University of the Philippines Diliman, Philippines 1101 rafal.rak@manchester.ac.uk.

Database : the Journal of Biological Databases and Curation

|July 10, 2014

Summary

This summary is machine-generated.

Web services enhance scientific literature processing. Argo workbench analytics for biochemical concepts in BioC format achieved top scores in the BioCreative challenge, showcasing interoperability.

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Published on: October 24, 2019

Area of Science:

Bioinformatics
Computational Biology
Text Mining

Background:

Web services are increasingly used for scientific literature processing.
Interoperability of Web services relies on suitable data exchange formats.
The biological domain requires domain-specific and generic representations.

Purpose of the Study:

To evaluate four interoperability formats (BioC, BioNLP, XMI, RDF) for biological Web services.
To demonstrate customizable Web service creation using the Argo text-mining workbench.
To assess the performance of automated analytics within Web services.

Main Methods:

Utilized the Argo Web-based text-mining workbench for customizable Web service creation.
Configured Web services to accept and produce various input/output data interchange formats.
Evaluated four interoperability formats: BioC, BioNLP, XMI, and RDF.
Participated in the BioCreative IV challenge to quantitatively evaluate automated analytics.

Main Results:

Achieved the highest combined scores among 10 teams in the BioCreative IV challenge for biochemical concept recognition.
Demonstrated 2-fold customization of Web services: pipeline construction and data format configuration.
Provided qualitative evaluation of the four considered interoperability formats.

Conclusions:

The Argo workbench facilitates the creation and deployment of customizable Web services for biological text mining.
BioC collections and associated analytics show high performance and interoperability for biochemical concept recognition.
The evaluated formats offer different strengths for domain-specific and generic scientific data exchange.