Patterns of International Coauthor Collaboration in Bioinformatics BJSTR


An interdisciplinary field of science developing schemes/ methods and software tools for understanding and utilizing biological data for health care is popular in recent years [1]. By searching keyword Bioinformatics from Medline library on October 31, 2017, we found 228,865 published papers in which 3,928 with bioinformatics in title. Bioinformatics combines computer science knowledge, statistics and engineering to analyze and interpret the biological data using mathematical and statistical techniques has become an important part of many areas of biology in a short span of time. However, the pattern of international coauthor collaboration as well as the main MESH (medical subject heading) term [2,3] is still unclear.

Aims of the Study

Our aims are to investigate journal features by collecting data from Medline and to visualize the journal characteristics of Bioinformatics in following representations:


Data Sources

We programed Microsoft Excel VBA (visual basic for applications) modules for extracting abstracts and their corresponding coauthor names as well as MESH terms on October 31, 2017 from the US National Library of Medicine National Institutes of Health (Medline) by a keyword “Bioinformatics”[Journal]. Only those abstracts published by Bioinformatics and labelled with Journal Article were included. Others like those labelled with Published Erratum, Editorial or without author name(s) were excluded from this study. A total of 11,411 abstracts were retrieved from Medline since 1999.

Data Arrangement to Fit SNA Requirement

We analyzed 11,411 papers with complete data including authors’ countries, names, and MESH terms. Prior to visualized representations of research findings using SNA, we organized data in compliance with the SNA format and guidelines using Pajek software [11]. Microsoft Excel VBA was used to arrange data fitting the SNA requirement.

Graphical Representations to Report

We combined SNA and Google Maps to present the distribution of nations and their corresponding collaborations by separating isolated and clustered nodes (e.g., nations). The bigger bubble means the more number of authors (including their coauthors) in papers. The wider line indicates the stronger relations between two nodes. Community clusters are filled with different colors in bubbles. Similarly, keywords of MESH terms represent the research domain for Bioinformatics, the stronger relations between two MESH terms can be highlighted through the SNA, like the concept of co-occurrence about beer and diapers sales. The presentation for the bubble and line is interpreted in results.

Statistical Tools and Data Analyses

Google Maps [12] and SNA Pajek software [11] were used to display visualized representations for Bioinformatics. Author-made Excel VBA modules were applied to organize data. Gini coefficient [13] is used to measure the strength of a role in a network: the higher is the Gini, the stronger is the role in the network.


Authors’ Nations and their Relations

A total of 11,411 papers with complete authors’ nations based on journal article since 1999 are collected. The most number of papers are from nations of U.S. (4175, 36.58%) and Germany (1010, 8.85%). The distribution of coauthor nations is present in Figure 1. The closest relation is linked by U.S. and Taiwan, see the widest line in (Figure 2). All coauthors connected to Taiwan can be shown in Figure 3. After we click the bubble and the diagram. Interested readers are recommended to practice it by clink the link in reference [14].

Keywords to Present the Journal Research Domain

The most linked Keywords denoted by MESH terms are algorithms, software, *algorithms sequence analysis, dna/*methods, information storage and netrieval/*methods, and sequence analysis/instrument/Methods, see (Figure 4). The closest relation is between algorithms and software with a highest frequency of 848. Two terms of algorithms and sequence alignment/*methods (760) follow [15].


In this study, we found that


Social network analysis provides wide and deep insight into the relationships among nations for coauthor collaborations. The results can be offered to authors who are interested in submission to the target journal.



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Biomedical Journal of Scientific & Technical Research (BJSTR) is a multidisciplinary, scholarly Open Access publisher focused on Genetic, Biomedical