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Related Experiment Video

Updated: May 18, 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

Peer2ref: a peer-reviewer finding web tool that uses author disambiguation.

Miguel A Andrade-Navarro¹, Gareth A Palidwor, Carol Perez-Iratxeta

¹Ottawa Hospital Research Institute, 501 Smyth Road, Ottawa, Ontario, K1H 8L6, Canada. cpereziratxeta@gmail.com.

|September 11, 2012

Summary

Finding suitable peer reviewers is challenging. The peer2ref method uses manuscript abstracts to identify experts by analyzing keywords and author bibliographies in MEDLINE, streamlining the reviewer selection process.

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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

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Last Updated: May 18, 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

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Area of Science:

Scientific Publishing
Scholarly Communication
Bibliometrics

Background:

Increasing research specialization complicates reviewer selection for scientific manuscripts.
Identifying appropriate peer reviewers is time-consuming and prone to author name ambiguity.

Purpose of the Study:

To develop an automated method supporting authors and editors in selecting suitable peer reviewers.
To address the challenges of finding qualified experts in a growing body of scientific literature.

Main Methods:

Developed peer2ref, a method utilizing manuscript abstracts for keyword extraction via fuzzy binary relations.
Searched extracted keywords against indexed author profiles derived from MEDLINE bibliographies.
Employed co-author disambiguation to ensure accurate scientist identification.

Main Results:

The peer2ref method successfully identifies potential peer reviewers based on manuscript content.
The system leverages MEDLINE data, including over 3,800 journals and authors from the last decade.
Automated expert suggestion facilitates efficient peer-review assignment.

Conclusions:

The peer2ref web server provides a publicly accessible tool for expert reviewer identification.
This method aids in overcoming challenges in scientific peer review by leveraging bibliometric data.