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Study of international anticancer research trends via co-word and document co-citation visualization analysis

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Abstract

The aim of this work is to make a bibliometric analysis of anticancer research literature based on the data from the Web of Science. Anticancer drug research references published from 2000 to 2014 were used. Citespace software was employed to generate the knowledge maps of country/institution, cited authors, cited journals, co-words and cited references related with anticancer drug research. Results of this analysis indicated that the USA is the most productive country and the Chinese Acad. Sci. is the most productive institution in this field. Maeda H is the most influential author, leading the highest citation author group. “CANCER RES” is the most cited journal in which the most influential anticancer drug research articles were published. Mosmann’s (1983) paper is a representative and symbolic reference with the highest co-citation of number of 146 (centrality 0.29). The five hot anticancer drug research topics were also disclosed; they are: (1) chemotherapy drugs, (2) drug delivery, (3) bioscreening, (4) drug resistance research, and (5) enzyme inhibitor studies. Research frontiers identified included drug delivery with nanoparticles, controlled release, metabolism and so on. These analyses will be valuable for the reader to grasp an overall picture of anticancer research and research trends during these years.

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References

  • Bradford, M. M. (1976). A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Analytical Biochemistry, 72(1/2), 248–254.

    Article  Google Scholar 

  • Chen, C. M. (2005). The centrality of pivotal points in the evolution of scientific networks. International Conference on Intelligent User Interfaces, Proceedings IUI: 98–105.

  • Chen, K. H., & Guan, J. C. (2011). A bibliometric investigation of research performance in emerging nanobiopharmaceuticals. Journal of Informetrics, 5(2), 233–247.

    Article  Google Scholar 

  • Chou, T. C. (1984). Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors. Advances in enzyme regulation, 22, 27.

    Article  Google Scholar 

  • Gref, R. (1994). Biodegradable long-circulating polymeric nanospheres. Science, 263, 1600.

    Article  Google Scholar 

  • Hao, D. C., Xiao, P. G., & Ge, G. B. (2012). Biological, chemical, and omics research of Taxus medicinal resources. Drug Development Research, 73(8), 477–486.

    Article  Google Scholar 

  • Li, X. (2001). New progress in the research of anticancer drugs. China Pharmacy, 7, 45–47.

    Google Scholar 

  • Liu, G. F., Sun, H. P., & Song, X. P. (2014). Visualizing and mapping the research on patents in information science and management science. Malaysian Journal of Library and Information Science, 19(1), 87–103.

    Google Scholar 

  • Lowry, O. H. (1951). Protein measurement with the folin phenol reagent. J Biological Chemistry, 193, 265.

    Google Scholar 

  • Maeda, H., Wu, J., Sawa, T., Matsumura, Y., & Hori, K. (2000). Tumor vascular permeability and the EPR effect in macromolecular therapeutics: a review. Journal of Controlled Release, 65, 271–284.

    Article  Google Scholar 

  • Matsumura, Y., & Maeda, H. (1986). A new concept for macromolecular therapeutics in cancer chemotherapy: Mechanism of tumoritropic accumulation of proteins and the antitumor agent smancs. Cancer Research, 46(12I), 6387–6392.

    Google Scholar 

  • Monks, A. (1991). Feasibility of a high-flux anticancer drug screen using a diverse panel of cultured human tumor cell lines. J Natl Cancer Inst, 83, 757.

    Article  Google Scholar 

  • Mosmann, T. (1983). Rapid colorimetric assay for cellular growth and survival: application to proliferation and cytotoxicity assays. Journal of Immunological Methods, 65(1-2), 55–63.

    Article  Google Scholar 

  • Niazi, M., & Hussain, A. (2011). Agent-based computing from multi-agent systems to agent-based models: a visual survey. Scientometrics, 89(2), 479–499.

    Article  Google Scholar 

  • Paull, K. D. (1989). Display and analysis of patterns of differential activity of drugs against human tumor cell lines: development of mean graph and Compare algorithm. Journal of the National Cancer Institute, 81, 1088.

    Article  Google Scholar 

  • Qian, G. (2012). Scientometrics analysis on the research field of wenchuan earthquake. Disaster Advances, 5(4), 704–707.

    Google Scholar 

  • Skehan, P., Storeng, R., Scudiero, D., et al. (1990). New colorimetric cytotoxicity assay for anticancer-drug screening. Journal of national cancer institute, 82(13), 1107–1112.

    Article  Google Scholar 

  • White, D.H. and McCain W. K. (1986–1998). Visualizing a discipline: an author co-citation analysis of information science, JASIST. 49.4: 327–355.

  • Zhang, X., Li, X. R., & Zhang, J. (2013). Current status and future perspectives of PI3 K and mTOR inhibitor as anticancer drugs in breast cancer. Current Cancer Drug Targets, 13(2), 175–187.

    Article  Google Scholar 

  • Zhang, H., Wang, X. J., & Gou, D. (2010). Statistical analysis of patent application of anticancer drug taxol. China Pharmacy, 36, 3376–3378.

    Google Scholar 

  • Zhou, Y. Y., Guo, Q. H., & Gu, X. X. (2004). Brief introduction to the research of dynamic anticancer drugs. Chemical Education, 5, 10–13.

    Google Scholar 

Download references

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Xie, P. Study of international anticancer research trends via co-word and document co-citation visualization analysis. Scientometrics 105, 611–622 (2015). https://doi.org/10.1007/s11192-015-1689-0

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