Visualizing Hot and Emerging Topics in Biochemistry and Molecular Biology in Iran

Gholampour, Behzad, Saboury, Ali Akbar and Noruzi, Alireza Visualizing Hot and Emerging Topics in Biochemistry and Molecular Biology in Iran. Iranian Journal of Information Processing and Management, 2020, vol. 35, n. 4, pp. 1119-1148. [Journal article (Paginated)]

[thumbnail of hot.topics.pdf]
Preview
Text
hot.topics.pdf

Download (3MB) | Preview

English abstract

The purpose of this descriptive research was to identify hot and emerging topics in Biochemistry and Molecular Biology in Iran and to map the intellectual structure of this field in a ten-year period. The intellectual structure of the field of Biochemistry and Molecular Biology in Iran was studied by analyzing co-occurrences of keywords and cited references. The research population of this study was all research and review papers of Iranian researchers published in journals indexed by the Web of Science database from 2008 to 2017. The collected data from Web of Science were analyzed by the CiteSpace Software in order to map the intellectual structure of this field. The results showed that the keywords such as gene expression, protein, in vitro, oxidative stress, binding, apoptosis and cell were among the hot research topics in Iran and terms such as chitosan, nanocomposite, antibacterial activity, dynamics molecules, stem cells, mesenchymal stem cells and immobilization have been indicative of the emerging topics in Iranian research in the studied time period. Increasing publications in the field of Biochemistry and Molecular Biology in Iran at the international level and its inclusion in the country's research priorities led us to conduct a scientometric study of this research area. Therefore, due to the hot and emerging topics identified in this research, such studies can be used as a road map for the country's large-scale scientific planning and policy.

Item type: Journal article (Paginated)
Keywords: Intellectual Structure, Keywords Co-occurrence, Cited References, Biochemistry and Molecular Biology, Hot Topics, Emerging Topics, Visualization, Iran
Subjects: B. Information use and sociology of information > BB. Bibliometric methods
Depositing user: Dr. Alireza Noruzi
Date deposited: 22 Aug 2020 08:34
Last modified: 22 Aug 2020 08:34
URI: http://hdl.handle.net/10760/40310

References

Bazm, S., Kalantar, S. M., & Mirzaei, M. (2016). Bibliometric mapping and clustering analysis of Iranian papers on reproductive medicine in Scopus database (2010-2014). International journal of reproductive biomedicine, 14(6), 371-382.

Bynum, W. 1999. A History of Molecular Biology. Nature Medicine, 5(2): 140. https://doi.org/10.1038/5498

Chen, C. 2016. CiteSpace: a practical guide for mapping scientific literature. New York: Nova Science Publishers, Incorporated. Riverside. Available at: https://www.researchgate.net/publication/308204148_CiteSpace_A_Practical_Guide_for_Mapping_Scientific_Literature

Chen C. 2016. How to Use CiteSpace. Lean Publishing, British Columbia, Canada.

Chen, C., I. Y. Song, X. Yuan & J. Zhang. 2008. The thematic and citation landscape of data and knowledge engineering (1985–2007). Data & Knowledge Engineering, 67(2): 234-259.‏

Chen, C. 2014. The CiteSpace Manual. Available at: http://cluster.ischool.drexel.edu/~cchen/citespace/CiteSpaceManual.pdf

Cheng, B. 2006. Using social network analyses to investigate potential bias in editorial peer review in core journals of comparative/international education. PhD dissertation, Brigham Young University.

Cheong, F. & B. J. Corbitt. 2009. A social network analysis of the co-authorship network of the Pacific Asia Conference on Information Systems from 1993 to 2008. PACIS 2009 Proceedings, 23.‏‏

Gholampour, S., Noruzi, A., Gholampour, B., & Elahi, A. (2019). Research trends and bibliometric analysis of a journal: Sport Management Review. Webology, 16(2), Article 200, 223-241.

Hatala, J. P. 2006. Social network analysis in human resource development: A new methodology. Human Resource Development Review, 5(1): 45-71.‏

Hou, J., X. Yang & C. Chen. 2018. Emerging trends and new developments in information science: A document co-citation analysis (2009–2016). Scientometrics, 115(2), 869-892.

‏Jin, Y. & S. Ji. 2018. Mapping hotspots and emerging trends of business model innovation under networking in Internet of Things. EURASIP Journal on Wireless Communications and Networking, (1): 96.

Jin, Y. & X. Li. 2018. Visualizing the hotspots and emerging trends of multimedia big data through scientometrics. Multimedia Tools and Applications, 1-25.

Jin, Y., S. Ji, X. Li & J. Yu. 2017. A scientometric review of hotspots and emerging trends in additive manufacturing. Journal of Manufacturing Technology Management, 28(1): 18-38.

Jin, Y., X. Li, R. I. Campbell & S. Ji. 2018. Visualizing the hotspots and emerging trends of 3D printing through scientometrics. Rapid Prototyping Journal, 24(5): 801-8012.

Kim, M. C., & C. Chen. 2015. A scientometric review of emerging trends and new developments in recommendation systems. Scientometrics, 104(1), 239-263.‏

Learned-Miller, E. G. 2013. Entropy and Mutual Information. United States: University of Massachusetts, Amherst, Department of Computer Science.

Li, X., H. Qiao & S. Wang. 2017. Exploring evolution and emerging trends in business model study: a co-citation analysis. Scientometrics, 111(2): 869-887.

Murray, R. K., D. K. Granner, P. A. Mayes & V. W. Rodwell. 2003. A lange medical book. Harper’s Illustrated Biochemistry. 26th ed. New York: McGraw-Hill Companies, Inc. Riverside.

Racherla, P. & C. Hu. 2010. A social network perspective of tourism research collaborations. Annals of Tourism Research, 37(4): 1012-1034.‏

Salton, G. & C. Buckley. 1988. term-weighting approaches in automatic text retrieval. Information processing & management, 24(5): 513-523.‏

Shen, S., C. Cheng, J. Yang & S. Yang. 2018. Visualized analysis of developing trends and hot topics in natural disaster research. PloS one, 13(1): e0191250.

Synnestvedt, M. B., C. Chen & J. H. Holmes. 2005. CiteSpace II: visualization and knowledge discovery in bibliographic databases. In AMIA Annual Symposium Proceedings (Vol. 2005, p. 724). American Medical Informatics Association.

Xiao, F., C. Li, J. Sun & L. Zhang. 2017. Knowledge domain and emerging trends in organic photovoltaic technology: A scientometric review based on CiteSpace analysis. Frontiers in chemistry, 5, 67.

Zhang, C., & J. Guan. 2017. How to identify metaknowledge trends and features in a certain research field? Evidences from innovation and entrepreneurial ecosystem. Scientometrics, 113(2): 1177-1197.


Downloads

Downloads per month over past year

Actions (login required)

View Item View Item