From systems to biology: A computational analysis of the research articles on systems biology from 1992 to 2013

PLoS One. 2018 Jul 25;13(7):e0200929. doi: 10.1371/journal.pone.0200929. eCollection 2018.

Abstract

Systems biology is a discipline that studies biological systems from a holistic and interdisciplinary perspective. It brings together biologists, mathematicians, computer scientists, physicists, and engineers, so it has both biology-oriented components and systems-oriented components. We applied several computational tools to analyze the bibliographic information of published articles in systems biology to answer the question: Did the research topics of systems biology become more biology-oriented or more systems-oriented from 1992 to 2013? We analyzed the metadata of 9923 articles on systems biology from the Web of Science database. We identified the most highly cited 330 references using computational tools and through close reading we divided them into nine categories of research types in systems biology. Interestingly, we found that articles in one category, namely, systems biology's applications in medical research, increased tremendously. This finding was corroborated by computational analysis of the abstracts, which also suggested that the percentages of topics on vaccines, diseases, drugs and cancers increased over time. In addition, we analyzed the institutional backgrounds of the corresponding authors of those 9923 articles and identified the most highly cited 330 authors over time. We found that before the mid-1990s, systems-oriented scientists had made the most referenced contributions. However, in recent years, researchers from biology-oriented institutions not only represented a huge percentage of the total number of researchers, but also had made the most referenced contributions. Notably, interdisciplinary institutions only produced a small percentage of researchers, but had made disproportionate contributions to this field.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomedical Research / statistics & numerical data*
  • Data Analysis
  • Internet
  • Metadata
  • Publications / statistics & numerical data*
  • Systems Biology*

Associated data

  • figshare/10.6084/m9.figshare.5422594

Grants and funding

ML was funded through a grant from National Science Foundation held at the Arizona State University under SES 1243575. YZ received funding from the China Scholarship Council under scholarship 2011635028. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.