Productivity and influence in bioinformatics: A bibliometric analysis using PubMed central - Song, Min; Kim, SuYeon; Zhang, Guo; Ding, Ying; Chambers, Tamy (Journal of the American Society for Information Science and Technology, 2014)
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.