Skip to main content
SpringerLink
Log in

Gatekeepers in knowledge transfer between science and technology: an exploratory study in the area of gene editing

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

Gene editing is an emerging technology that is promising for the prevention and treatment of human diseases. This paper reports an exploratory study of networks of authors of scientific research publications and of inventors involved in patents during the years 2000–2019 in the area of gene editing. We use patents to represent technological output and their non-patent references to represent scientific output that transferred knowledge to the technological output. We apply social network analysis to identify gatekeepers on the boundary of science and technology. We find that author–inventors are crucial for network-wide knowledge transfer as they connect parts of the network that are otherwise disconnected, and can thus be considered gatekeepers, they occupy prominent positions in the co-authorship and co-invention networks. In the area of gene editing, gatekeepers emerged during 2007–2013 and increased significantly in number during 2014–2019. Our results suggest that there are differences in the brokerage role of gatekeepers identified by different indicators. Top gatekeepers identified by betweenness and Q-measure are in areas with intensive knowledge flow among authors and inventors, whereas gatekeepers occupying more structural hole may be in areas with sparse knowledge flow.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. More details can be found on the website: https://ghr.nlm.nih.gov/primer/genomicresearch/genomeediting.

References

  • Akcakaya, P., Bobbin, M. L., Guo, J. A., et al. (2018). In vivo CRISPR editing with no detectable genome—Wide off-target mutations. Nature,561(7723), 416–419.

    Google Scholar 

  • Alcacer, J., Gittelman, M., & Sampat, B. N. (2009). Applicant and examiner citations in US patents: An overview and analysis. Research Policy,38(2), 415–427.

    Google Scholar 

  • Antes, A. L., Mart, A., & Dubois, J. M. (2016). Are leadership and management essential for good research? An interview study of genetic researchers. Journal of Empirical Research on Human Research Ethics,11(5), 408–423.

    Google Scholar 

  • Belso Martinez, J. A., Molina Morale, F. X., & Martinez, C. L. (2015). Contributions of brokerage roles to firms’ innovation in a confectionery cluster. Technology Analysis & Strategic Management,27(9), 1014–1030.

    Google Scholar 

  • Bhattacharya, S., & Meyer, M. (2003). Large firms and the science–technology interface patents, patent citations, and scientific output of multinational corporations in thin films. Scientometrics,58(2), 265–279.

    Google Scholar 

  • Boyack, K. W., & Klavans, R. (2008). Measuring science–technology interaction using rare inventor–author names. Journal of Informetrics,2(3), 173–182.

    Google Scholar 

  • Breschi, S., & Catalini, C. (2010). Tracing the links between science and technology: An exploratory analysis of scientists’ and inventors’ networks. Research Policy,39(1), 26.

    Google Scholar 

  • Bu, Q. X. (2019). Reassess the law and ethics of heritable genome editing interventions: Lessons for China and the world. Issues in Law and Medicine,34(2), 115–146.

    Google Scholar 

  • Burt, R. S. (1992). Structural holes: The social structure of competition. Cambridge: Harvard University Press.

    Google Scholar 

  • Camillis, D. C., Bligny, J. C., Pennington, D., et al. (2012). Outcomes of the second workshop of the food sustainable consumption and production round table working group 1: Deriving scientifically sound rules for a sector-specific environmental assessment methodology. International Journal of Life Cycle Assessment,17(4), 511–515.

    Google Scholar 

  • Cassiman, B., et al. (2007). Measuring industry–science links through inventor–author relations: A profiling methodology. Scientometrics,70(2), 379–391.

    Google Scholar 

  • Chen, C. H. (2012). Factors influencing creativity in business innovation: From the perspective of csikszentmihalyi’s creativity system. In Proceedings of the 6th international conference of technology, education and development (Inted). Spain: Valencia.

  • Chen, Y., Yu, J., Niu, Y., et al. (2017). Modeling rett syndrome using talen-edited mecp2 mutant cynomolgus monkeys. Cell,169(3), 945–955.

    Google Scholar 

  • Cockburn, I. M., & Henderson, R. M. (1998). Absorptive capacity, coauthoring behavior, and the organization of research in drug discovery. Journal of Industrial Economics,46(2), 157–182.

    Google Scholar 

  • Cong, L., Ran, F. A., Cox, D., et al. (2013). Multiplex genome engineering using CRISPR–Cas systems. Science,339(6121), 819–823.

    Google Scholar 

  • Cyranoski, & David, (2016). CRISPR gene-editing tested in a person for the first time. Nature,539(7630), 479.

    Google Scholar 

  • De Solla Price, D. J. (1963). Little science, big science– and beyond. New York: Columbia University Press.

    Google Scholar 

  • De Solla Price, D. J. (1965). Is technology historically independent of science? A study in statistical historiography. Technology and Culture,6(4), 553–568.

    Google Scholar 

  • Ductor, L., et al. (2014). Social networks and research output. Review of Economics and Statistics,96(5), 936–948.

    Google Scholar 

  • Flom, P. L., Friedman, S. R., Strauss, S., et al. (2004). A new measure of linkage between two sub-networks. Connections,26(1), 62–70.

    Google Scholar 

  • Freeman, L. C. (1979). Centrality in social networks’ conceptual clarification. Social Networks,1(3), 215–239.

    MathSciNet  Google Scholar 

  • Gallo, A., Weijer, C., White, A., et al. (2012). What is the role and authority of gatekeepers in cluster randomized trials in health research? Trials,13(1), 116.

    Google Scholar 

  • Gittelman, M., & Kogut, B. (2003). Does good science lead to valuable knowledge? Biotechnology firms and the evolutionary logic of citation patterns. Management Science,49(4), 366–382.

    Google Scholar 

  • Goel, R. K., & Rich, D. P. (2005). Organization of markets for science and technology. Journal of Institutional and Theoretical Economics,161(1), 1–32.

    Google Scholar 

  • Graf, H. (2011). Gatekeepers in regional networks of innovators. Cambridge Journal of Economics,35(1), 173–198.

    Google Scholar 

  • Guns, R., Liu, Y. X., & Mahbuba, D. (2011). Q-measures and betweenness centrality in a collaboration network: A case study of the field of informetrics. Scientometrics,87(1), 133–147.

    Google Scholar 

  • Guterman, L. (2018). Gene-editing tool shows promise. Science,361(6407), 1053.

    Google Scholar 

  • Han, Z. M., Wu, Y., Tan, X. S., et al. (2015). Ranking key nodes in complex networks by considering structural holes. Acta physica sinica,64(5), 058902.

    Google Scholar 

  • Hofmann, B. (2018). The gene-editing of super-ego. Medicine, Health Care and Philosophy,21(3), 295–302.

    Google Scholar 

  • Hu, X. J., & Rousseau, R. (2018). A new approach to explore the knowledge transition path in the evolution of science & technology: From the biology of restriction enzymes to their application in biotechnology. Journal of informetrics,12(3), 842–857.

    Google Scholar 

  • Huang, Y., Porter, A., Zhang, Y., et al. (2019). Collaborative networks in gene editing. Nature Biotechnology,7, 1107–1109.

    Google Scholar 

  • Hylton, K. N. (2016). Patent uncertainty: Toward a framework with applications. Boston University Law Review,96(3), 1117–1148.

    Google Scholar 

  • Jiang, J. M., et al. (2019). Knowledge flows from business method software patents: Influence of firms’ global social networks. Journal of Technology Transfer,44(4), 1070–1096.

    Google Scholar 

  • Jinek, M., Jiang, F., Taylor, D. W., et al. (2014). Structures of cas9 endonucleases reveal rna-mediated conformational activation. Science,343(6176), 1247997.

    Google Scholar 

  • Kim, B., Kim, E., Miller, D. J., et al. (2016). The impact of the timing of patents on innovation performance. Research Policy,45(4), 914–928.

    Google Scholar 

  • Knott, G. J., & Doudna, J. A. (2018). CRISPR–Cas guides the future of genetic engineering. Science,361(6405), 866–869.

    Google Scholar 

  • Kordsmeier, G. T. (2018). Social forces and decision-making by gatekeepers in arts organizations. Sociology Compass,12(7), e12594.

    Google Scholar 

  • Li, H. J., Haurigot, V., Doyon, Y., et al. (2011). In vivo genome editing restores haemostasis in a mouse model of haemophilia. Nature,475(7355), 217-U128.

    Google Scholar 

  • Long, C. Z., Amoasii, L., Mireault, A. A., et al. (2015). Postnatal genome editing partially restores dystrophin expression in a mouse model of muscular dystrophy. Science,351(6271), 400.

    Google Scholar 

  • Maraut, S., & Martinez, C. (2014). Identifying author–inventors from Spain: Methods and a first insight into results. Scientometrics,101(1), 445–476.

    Google Scholar 

  • Meissner, D., & Shmatko, N. (2017). “keep open”: The potential of gatekeepers for the aligning universities to the new knowledge triangle. Technological Forecasting & Social Change,123, 191–198.

    Google Scholar 

  • Meyer, M. (2006). Are patenting scientists the better scholars? An exploratory comparison of inventor–authors with their non-inventing peers in nano-science and technology. Research Policy,35(10), 1646–1662.

    Google Scholar 

  • Miller, K., et al. (2018). Entrepreneurial academics and academic entrepreneurs: A systematic literature review. International Journal of Technology Management,77(1–3), 9–37.

    Google Scholar 

  • Miyagi, A., Lu, A., & Humphreys, B. D. (2016). Gene editing: Powerful new tools for nephrology research and therapy. Journal of the American Society of Nephrology,27(10), 2940–2947.

    Google Scholar 

  • Nelson, C. E., Hakim, C. H., Ousterout, D. G., et al. (2015). In vivo genome editing improves muscle function in a mouse model of Duchenne muscular dystrophy. Science,351(6271), 403–407.

    Google Scholar 

  • Otte, E., & Rousseau, R. (2002). Social network analysis: A powerful strategy, also for the information sciences. Journal of Information Science,28(6), 441–453.

    Google Scholar 

  • Robert, C. (2013). Genetic microsurgery for the masses. Science,342(6165), 1434–1435.

    Google Scholar 

  • Rousseau, R., Liu, Y. X., & Guns, R. (2013). Mathematical properties of Q-measures. Journal of Informetrics,7(3), 737–745.

    Google Scholar 

  • Rousseau, R., & Zhang, L. (2008). Betweenness centrality and q-measures in directed valued networks. Scientometrics,75(3), 575–590.

    Google Scholar 

  • Tabebordbar, M., Zhu, K., Cheng, J., et al. (2015). In vivo gene editing in dystrophic mouse muscle and muscle stem cells. Science,351(6271), 407–411.

    Google Scholar 

  • Travis, J. (2015). Making the cut. Science,350(6267), 1456–1457.

    Google Scholar 

  • Wang, G., & Guan, J. (2011). Measuring science–technology interactions using patent citations and author–inventor links: An exploration analysis from Chinese nanotechnology. Journal of Nanoparticle Research,13(12), 6245–6262.

    Google Scholar 

  • Wang, F. F., Jia, C. R., Wang, X. H., et al. (2019). Exploring all-author tripartite citation networks: A case study of gene editing. Journal of Informetrics,13(3), 856–873.

    MathSciNet  Google Scholar 

  • Wang, X. W., Zhang, X., & Xu, S. M. (2011). Patent co-citation networks of fortune 500 companies. Scientometrics,88(3), 761–770.

    Google Scholar 

  • Zamzami, N., et al. (2015). Evaluating the science–technology interaction in nanotechnology: A simulation-based study. In Proceedings of the winter simulation conference (WSC), CA, USA.

  • Zhang, G. J., Liu, L. N., & Wei, F. F. (2019). Key nodes mining in the inventor–author knowledge diffusion network. Scientometrics,118(3), 721–735.

    Google Scholar 

  • Zhou, Y., Sharma, J., Ke, Q., et al. (2019). Atypical behaviour and connectivity in SHANK3-mutant macaques. Nature,570(7761), 326.

    Google Scholar 

  • Zhu, Z., Li, Q., Lee, K., et al. (2016). Genome editing of lineage determinants in human pluripotent stem cells reveals mechanisms of pancreatic development and diabetes. Cell Stem Cell,18(6), 755–768.

    Google Scholar 

  • Zucker, L. G., et al. (2002). Commercializing knowledge: University science, knowledge capture, and firm performance in biotechnology. Management Science,48(1), 138–153.

    Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China, Grant Numbers 71573225 and 71974167. The authors would like to thank anonymous reviewers for their constructive remarks.

Author information

Authors and Affiliations

  1. Medical Information Center, and Department of Neurology of Affiliated Hospital 2, Zhejiang University School of Medicine, Hangzhou, 310058, China

    Xian Li & Xiaojun Hu

  2. School of Library and Information Studies, University of Alberta, Edmonton, Canada

    Dangzhi Zhao

Authors
  1. Xian Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dangzhi Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiaojun Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaojun Hu.

Ethics declarations

Conflict interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, X., Zhao, D. & Hu, X. Gatekeepers in knowledge transfer between science and technology: an exploratory study in the area of gene editing. Scientometrics 124, 1261–1277 (2020). https://doi.org/10.1007/s11192-020-03537-y

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-020-03537-y

Keywords

Search

Navigation