Productivity and influence in bioinformatics: A bibliometric analysis using PubMed central
Bioinformatics is a fast‐growing field based on the optimal use of “big data” gathered in genomic, proteomics, and functional genomics research. In this paper, we conduct a comprehensive and in‐depth bibliometric analysis of the field of bioinformatics by extracting citation data from PubMed Central...
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| Published in | Journal of the American Society for Information Science and Technology Vol. 65; no. 2; pp. 352 - 371 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Malden, MA
Blackwell Publishing Ltd
01.02.2014
Wiley Wiley Periodicals Inc |
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| Online Access | Get full text |
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| Abstract | Bioinformatics is a fast‐growing field based on the optimal use of “big data” gathered in genomic, proteomics, and functional genomics research. In this paper, we conduct a comprehensive and in‐depth bibliometric analysis of the field of bioinformatics by extracting citation data from PubMed Central full‐text. Citation data for the period 2000 to 2011, comprising 20,869 papers with 546,245 citations, was used to evaluate the productivity and influence of this emerging field. Four measures were used to identify productivity; most productive authors, most productive countries, most productive organizations, and most popular subject terms. Research impact was analyzed based on the measures of most cited papers, most cited authors, emerging stars, and leading organizations. Results show the overall trends between the periods 2000 to 2003 and 2004 to 2007 were dissimilar, while trends between the periods 2004 to 2007 and 2008 to 2011 were similar. In addition, the field of bioinformatics has undergone a significant shift, co‐evolving with other biomedical disciplines. |
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| AbstractList | Bioinformatics is a fast‐growing field based on the optimal use of “big data” gathered in genomic, proteomics, and functional genomics research. In this paper, we conduct a comprehensive and in‐depth bibliometric analysis of the field of bioinformatics by extracting citation data from
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entral full‐text. Citation data for the period 2000 to 2011, comprising 20,869 papers with 546,245 citations, was used to evaluate the productivity and influence of this emerging field. Four measures were used to identify productivity; most productive authors, most productive countries, most productive organizations, and most popular subject terms. Research impact was analyzed based on the measures of most cited papers, most cited authors, emerging stars, and leading organizations. Results show the overall trends between the periods 2000 to 2003 and 2004 to 2007 were dissimilar, while trends between the periods 2004 to 2007 and 2008 to 2011 were similar. In addition, the field of bioinformatics has undergone a significant shift, co‐evolving with other biomedical disciplines. Bioinformatics is a fast‐growing field based on the optimal use of “big data” gathered in genomic, proteomics, and functional genomics research. In this paper, we conduct a comprehensive and in‐depth bibliometric analysis of the field of bioinformatics by extracting citation data from PubMed Central full‐text. Citation data for the period 2000 to 2011, comprising 20,869 papers with 546,245 citations, was used to evaluate the productivity and influence of this emerging field. Four measures were used to identify productivity; most productive authors, most productive countries, most productive organizations, and most popular subject terms. Research impact was analyzed based on the measures of most cited papers, most cited authors, emerging stars, and leading organizations. Results show the overall trends between the periods 2000 to 2003 and 2004 to 2007 were dissimilar, while trends between the periods 2004 to 2007 and 2008 to 2011 were similar. In addition, the field of bioinformatics has undergone a significant shift, co‐evolving with other biomedical disciplines. Bioinformatics is a fast-growing field based on the optimal use of "big data" gathered in genomic, proteomics, and functional genomics research. In this paper, we conduct a comprehensive and in-depth bibliometric analysis of the field of bioinformatics by extracting citation data from PubMed Central full-text. Citation data for the period 2000 to 2011, comprising 20,869 papers with 546,245 citations, was used to evaluate the productivity and influence of this emerging field. Four measures were used to identify productivity; most productive authors, most productive countries, most productive organizations, and most popular subject terms. Research impact was analyzed based on the measures of most cited papers, most cited authors, emerging stars, and leading organizations. Results show the overall trends between the periods 2000 to 2003 and 2004 to 2007 were dissimilar, while trends between the periods 2004 to 2007 and 2008 to 2011 were similar. In addition, the field of bioinformatics has undergone a significant shift, co-evolving with other biomedical disciplines. [PUBLICATION ABSTRACT] Bioinformatics is a fast-growing field based on the optimal use of 'big data' gathered in genomic, proteomics, and functional genomics research. In this paper, we conduct a comprehensive and in-depth bibliometric analysis of the field of bioinformatics by extracting citation data from PubMed Central full-text. Citation data for the period 2000 to 2011, comprising 20,869 papers with 546,245 citations, was used to evaluate the productivity and influence of this emerging field. Four measures were used to identify productivity; most productive authors, most productive countries, most productive organizations, and most popular subject terms. Research impact was analyzed based on the measures of most cited papers, most cited authors, emerging stars, and leading organizations. Results show the overall trends between the periods 2000 to 2003 and 2004 to 2007 were dissimilar, while trends between the periods 2004 to 2007 and 2008 to 2011 were similar. In addition, the field of bioinformatics has undergone a significant shift, co-evolving with other biomedical disciplines. [Copyright Wiley Periodicals Inc.] |
| Author | Ding, Ying Kim, SuYeon Zhang, Guo Song, Min Chambers, Tamy |
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| References_xml | – reference: Baldi, P., & Brunak, S. (2001). Bioinformatics: The machine learning approach (2nd ed.). Cambridge, MA: MIT Press. – reference: Ding, Y. (2010). Semantic web: Who is who in the field-a bibliometric analysis. Journal of Information Science, 36(3), 335-356. – reference: Nicolaisen, J. (2007). Citation analysis. Annual Review of Information Science and Technology, 41(1), 609-641. – reference: Bornmann, L., Mutz, R., Neuhaus, C., & Daniel, H.-D. (2008). Citation counts for research evaluation: Standards of good practice for analyzing bibliometric data and presenting and interpreting results. Ethics in Science and Environmental Politics, 8, 93-102. – reference: Small, H. (2011). Interpreting maps of science using citation context sentiments: A preliminary investigation. Scientometrics, 87, 373-388. – reference: Cronin, B. (1984). The citation process: The role and significance of citations in scientific communication. London: Taylor Graham. – reference: Patra, S.K., & Mishra, S. (2006). Bibliometric study of bioinformatics literature. Scientometrics, 67(3), 477-489. – reference: Yan, E., & Ding, Y. (2010). Weighted citation: An indicator of an article's prestige. Journal of the American Society for Information Science and Technology, 61(8), 1635-1643. – reference: Glänzel, W., Thijs, B., Schubert, A., & Debackere, K. (2009). Subfield specific normalized relative parameters and a new generation of relational charts: Methodological foundations illustrated on the assessment of institutional research performance. Scientometrics, 78(1), 165-188. – reference: McCain, K.W. (1990). Mapping authors in intellectual space: A technical overview. Journal of the American Society for Information Science, 41(6), 433-443. – reference: Cronin, B. (2004). Normative shaping of scientific practice: The magic of Merton. Scientometrics, 60(1), 41-46. – reference: Garfield, E. (1955). 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| Snippet | Bioinformatics is a fast‐growing field based on the optimal use of “big data” gathered in genomic, proteomics, and functional genomics research. In this paper,... Bioinformatics is a fast-growing field based on the optimal use of "big data" gathered in genomic, proteomics, and functional genomics research. In this paper,... Bioinformatics is a fast-growing field based on the optimal use of 'big data' gathered in genomic, proteomics, and functional genomics research. In this paper,... |
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| SubjectTerms | Author productivity Bibliometrics Bibliometrics. Scientometrics Bibliometrics. Scientometrics. Evaluation Bioinformatics Biology Citation analysis Data Exact sciences and technology Impact analysis Information and communication sciences Information retrieval Information science. Documentation Library and information science. General aspects Optimization Organizations Productivity Proteomics Sciences and techniques of general use Studies text mining Trends |
| Title | Productivity and influence in bioinformatics: A bibliometric analysis using PubMed central |
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