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Tracking the emergence of synthetic biology

Author

Listed:
  • Philip Shapira

    (University of Manchester
    Georgia Institute of Technology
    University of Manchester)

  • Seokbeom Kwon

    (Georgia Institute of Technology
    Georgia Institute of Technology)

  • Jan Youtie

    (Georgia Institute of Technology)

Abstract

Synthetic biology is an emerging domain that combines biological and engineering concepts and which has seen rapid growth in research, innovation, and policy interest in recent years. This paper contributes to efforts to delineate this emerging domain by presenting a newly constructed bibliometric definition of synthetic biology. Our approach is dimensioned from a core set of papers in synthetic biology, using procedures to obtain benchmark synthetic biology publication records, extract keywords from these benchmark records, and refine the keywords, supplemented with articles published in dedicated synthetic biology journals. We compare our search strategy with other recent bibliometric approaches to define synthetic biology, using a common source of publication data for the period from 2000 to 2015. The paper details the rapid growth and international spread of research in synthetic biology in recent years, demonstrates that diverse research disciplines are contributing to the multidisciplinary development of synthetic biology research, and visualizes this by profiling synthetic biology research on the map of science. We further show the roles of a relatively concentrated set of research sponsors in funding the growth and trajectories of synthetic biology. In addition to discussing these analyses, the paper notes limitations and suggests lines for further work.

Suggested Citation

  • Philip Shapira & Seokbeom Kwon & Jan Youtie, 2017. "Tracking the emergence of synthetic biology," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1439-1469, September.
    • Handle: RePEc:spr:scient:v:112:y:2017:i:3:d:10.1007_s11192-017-2452-5
    DOI: 10.1007/s11192-017-2452-5
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    Cited by:

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    2. Seokbeom Kwon & Jan Youtie & Alan Porter & Nils Newman, 2024. "How does regulatory uncertainty shape the innovation process? Evidence from the case of nanomedicine," The Journal of Technology Transfer, Springer, vol. 49(1), pages 262-302, February.
    3. Baaden, Philipp & Rennings, Michael & John, Marcus & Bröring, Stefanie, 2024. "On the emergence of interdisciplinary scientific fields: (how) does it relate to science convergence?," Research Policy, Elsevier, vol. 53(6).
    4. Na Liu & Philip Shapira & Xiaoxu Yue, 2021. "Tracking developments in artificial intelligence research: constructing and applying a new search strategy," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3153-3192, April.
    5. Alejandro Martínez & Juan Carlos Henao & Mario A. Pinzón Camargo, 2021. "Disrupción tecnológica, transformación digital y sociedad. Tomo I, ¿Cuarta revolución industrial? : contribuciones tecnosociales para la transformación social," Books, Universidad Externado de Colombia, Facultad de Derecho, number 1280.
    6. Li Tang & Jennifer Kuzma & Xi Zhang & Xinyu Song & Yin Li & Hongxu Liu & Guangyuan Hu, 2023. "Synthetic biology and governance research in China: a 40-year evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5293-5310, September.
    7. Kwon, Seokbeom & Liu, Xiaoyu & Porter, Alan L. & Youtie, Jan, 2019. "Research addressing emerging technological ideas has greater scientific impact," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    8. Scott L. Greer & Benjamin Trump, 2019. "Regulation and regime: the comparative politics of adaptive regulation in synthetic biology," Policy Sciences, Springer;Society of Policy Sciences, vol. 52(4), pages 505-524, December.
    9. Ribeiro, Barbara & Shapira, Philip, 2019. "Anticipating governance challenges in synthetic biology: Insights from biosynthetic menthol," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 311-320.
    10. Porter, Alan L. & Chiavetta, Denise & Newman, Nils C., 2020. "Measuring tech emergence: A contest," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    11. Ribeiro, Barbara & Shapira, Philip, 2020. "Private and public values of innovation: A patent analysis of synthetic biology," Research Policy, Elsevier, vol. 49(1).
    12. Bordoloi, Tausif & Shapira, Philip & Mativenga, Paul, 2022. "Policy interactions with research trajectories: The case of cyber-physical convergence in manufacturing and industrials," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    13. Leonid Gokhberg & Dirk Meissner & Ilya Kuzminov, 2023. "What semantic analysis can tell us about long term trends in the global STI policy agenda," The Journal of Technology Transfer, Springer, vol. 48(6), pages 2249-2277, December.
    14. Juliana A. Ivar do Sul & Alexander S. Tagg & Matthias Labrenz, 2018. "Exploring the common denominator between microplastics and microbiology: a scientometric approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 2145-2157, December.
    15. Li, Munan & Porter, Alan L. & Suominen, Arho & Burmaoglu, Serhat & Carley, Stephen, 2021. "An exploratory perspective to measure the emergence degree for a specific technology based on the philosophy of swarm intelligence," Technological Forecasting and Social Change, Elsevier, vol. 166(C).

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    More about this item

    Keywords

    Emerging technology; Synthetic biology; Bibliometric analysis; Search strategy; Map of science; Research sponsors;
    All these keywords.

    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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