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

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 sev...

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Detalles Bibliográficos
Autores principales: Zou, Yawen, Laubichler, Manfred D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6059489/
https://www.ncbi.nlm.nih.gov/pubmed/30044828
http://dx.doi.org/10.1371/journal.pone.0200929
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author Zou, Yawen
Laubichler, Manfred D.
author_facet Zou, Yawen
Laubichler, Manfred D.
author_sort Zou, Yawen
collection PubMed
description 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.
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spelling pubmed-60594892018-08-09 From systems to biology: A computational analysis of the research articles on systems biology from 1992 to 2013 Zou, Yawen Laubichler, Manfred D. PLoS One Research Article 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. Public Library of Science 2018-07-25 /pmc/articles/PMC6059489/ /pubmed/30044828 http://dx.doi.org/10.1371/journal.pone.0200929 Text en © 2018 Zou, Laubichler http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Zou, Yawen
Laubichler, Manfred D.
From systems to biology: A computational analysis of the research articles on systems biology from 1992 to 2013
title From systems to biology: A computational analysis of the research articles on systems biology from 1992 to 2013
title_full From systems to biology: A computational analysis of the research articles on systems biology from 1992 to 2013
title_fullStr From systems to biology: A computational analysis of the research articles on systems biology from 1992 to 2013
title_full_unstemmed From systems to biology: A computational analysis of the research articles on systems biology from 1992 to 2013
title_short From systems to biology: A computational analysis of the research articles on systems biology from 1992 to 2013
title_sort from systems to biology: a computational analysis of the research articles on systems biology from 1992 to 2013
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6059489/
https://www.ncbi.nlm.nih.gov/pubmed/30044828
http://dx.doi.org/10.1371/journal.pone.0200929
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