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  • × author_ss:"Huang, S."
  • × author_ss:"Rousseau, R."
  1. Yang, B.; Rousseau, R.; Wang, X.; Huang, S.: How important is scientific software in bioinformatics research? : a comparative study between international and Chinese research communities (2018) 0.00 
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    Abstract
    Software programs are among the most important tools in data-driven research. The popularity of well-known packages and corresponding large numbers of citations received bear testimony of the contribution of scientific software to academic research. Yet software is not generally recognized as an academic outcome. In this study, a usage-based model is proposed with varied indicators including citations, mentions, and downloads to measure the importance of scientific software. We performed an investigation on a sample of international bioinformatics research articles, and on a sample from the Chinese community. Our analysis shows that scientists in the field of bioinformatics rely heavily on scientific software: the major differences between the international community and the Chinese example being how scientific packages are mentioned in publications and the time gap between the introduction of a package and its use. Biologists publishing in international journals tend to apply the latest tools earlier; Chinese scientists publishing in Chinese tend to follow later. Further, journals with higher impact factors tend to publish articles applying the latest tools earlier.
    Type
    a
  2. Yan, S.; Rousseau, R.; Huang, S.: Contributions of chinese authors in PLOS ONE (2016) 0.00 
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    Abstract
    Beginning with a short review of Public Library of Science (PLOS) journals, we focus on PLOS ONE and more specifically the contributions of Chinese authors to this journal. It is shown that their contribution is growing exponentially. In 2013 almost one fifth of all publications in this journal had at least one Chinese author. The average number of citations per publication is approximately the same for articles with a Chinese author and for articles without any Chinese coauthor. Using the odds-ratio, we could not find arguments that Chinese authors in PLOS ONE excessively cite other Chinese contributions.
    Type
    a

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