Growth Dynamics Study of Proteomics Research Output Since 2000 to 2018
Authors
-
Shyampur Siddheswari Mahavidyalaya, Ajodhya, Howrah − 711312, West Bengal, India; and Research Scholar, Department of Library and Information Science, Vidyasagar University, Midnapore − 721102, West Bengal
Soumen Teli -
Department of Library and Information Science, Vidyasagar University, Midnapore − 721102, West BengalBidyarthi Dutta
DOI:
https://doi.org/10.17821/srels/2020/v57i4/151623Keywords:
De Solla Price’s Theory, Exponential Model, Global Proteomics Research, Growth Dynamics Study, Growth of Literature, Logistic Model, Proteomics ResearchAbstract
Proteomics is the large scale of study of proteins with their function and structure. It is an approach for studying changes in metabolism in response to different stress conditions. It indicates the entire set of proteins that is, or can be, expressed by a genome, cell, tissue, or organism at a certain time. In India, the term ‘Proteomics’ was first used in an article on genomics in 1999. This paper presents the growth dynamics study of Indian and global proteomics research output with a comparative analysis. The growth pattern in India during 1999 to 2007 was exponential in nature followed by saturating power model, while the same for global research showed exponential pattern, followed by the saturating logarithmic curve. The speed of Indian growth was fast compared to global growth since after 2008 as evident from the magnitudes of AIS/AGS. The growth patterns followed Price’s law with an initial exponential trend followed by saturation thereafter. The magnitudes of the Activity Index over the years shows that Indian proteomics research is still far below the world average level, though the lowest AI in the year 2001 (0.002) escalated 19.5 times in 2015 (0.039). The Attractivity Index (AAI) values are found less than one indicating lower than world average impact values of Indian proteomics research, though it is continuously growing.
Downloads
Metrics
References
Bala, A. and Gupta, B.M. (2010). Mapping of Indian neuroscience research: A scientometric analysis of research output during 1999-2008. Neurology India. 58(1): 35. https://doi.org/10.4103/0028-3886.60393. PMid: 20228461.
Baskaran, C. (2013). Scientometric analysis of cryptography research output. SRELS Journal of Information Management. 50(4): 413-21.
Bhasin, V.K. (2000). Proteomics could be key in battle against malaria. Nature. 403(6771): 698. https://doi.org/10.1038/35001753. PMid: 10693775.
Braun, T., Schubert, A.P. and Kostoff, R.N. (2000). Growth and trends of Fullerene research as reflected in its journal literature. Chemical Reviews. 100(1): 23-38. https://doi.org/10.1021/cr990096j. PMid: 11749233.
Chandrasekhar, K.D.A., Lebonah, D.E. and Pramoda Kumari, J.A. (2014). Short review on proteomics and its applications. International Letters of Natural Sciences. 12(1): 77-84. https://doi.org/10.18052/www.scipress.com/ ILNS.17.77.
Devi, M. (2015). Scientometric analysis of growth of literature in nuclear medicine. History. 21(74): 511-20.
Dhawan, S.M., Gupta, B.M. and Bhusan, S. (2018). Global publications output in quantum computing research: A scientometric assessment during 2007-16. Emerging Science Journal. 2(4): 228-37. https://doi.org/10.28991/ esj-2018-01147.
Dutt, B. and Nikam, K. (2013). Solar cell research in India: a scientometric profile. Annals of Library and Information Studies. 60(2): 115-27.
Dutta, B. and Rath, D.S. (2013). Cosmology research in India: A scientometric study. Library Philosophy and Practice (e-journal). 996. https://digitalcommons.unl.edu/libphilprac/996.
Dutta, B. and Rath, D.S. (2013). Scientometric study of carbon nanotube research in India. SRELS Journal of Information Management. 50(5): 639-55.
Elango, B., Rajendran, P. and Bornmann, L. (2013). Global nanotribology research output (1996-2010): A scientometric analysis. PLoS One. 8(12), e81094. https://doi.org/10.1371/journal.pone.0081094. PMid: 24339900, PMCid: PMC3855179.
Garg, K. and Sharma, P. (1991). Solar power research: A scientometric study of world literature. Scientometrics. 21(2): 147-57. https://doi.org/10.1007/BF02017565.
Gupta, B.M. and Karisiddappa, C.R. (2000). Modeling the growth of literature in the area of theoretical population genetics. Scientometrics. 49(2): 321-55. https://doi.org/10.1023/A:1010577321082.
Gupta, P.K., Roy, J.K. and Prasad, M. (1999). DNA chips, microarrays and genomics. Current Science. 77: 875-84.
Hu, Y., et al. (2014). A scientometric study of global electric vehicle research. Scientometrics. 98(2): 1269-82. https://doi.org/10.1007/s11192-013-1067-8.
Jain, A. and Garg, K. (1992). Laser research in India: scientometric study and model projections. Scientometrics. 23(3): 395-415. https://doi.org/10.1007/ BF02029806.
Kademani, B.S. et al. (2006). Scientometric dimensions of Thorium research in India. DESIDOC Bulletin of Information Technology. 26(3): 9-25.
Kahn, P. (1995). Molecular biology: from genome to proteome: Looking at a cell’s proteins. Science. 270(5235): 369-70. https://doi.org/10.1126/science.270.5235.369. PMid: 7569989.
Karpagam, R. et al. (2011). Mapping of nanoscience and nanotechnology research in India: A scientometric analysis, 1990-2009. Scientometrics. 89(2):, 501. https://doi.org/10.1007/s11192-011-0477-8.
Konur, O. (2012). The scientometric evaluation of the research on the production of bioenergy from biomass. Biomass and Bioenergy. 47: 504-15. https://doi.org/10.1016/j.biombioe.2012.09.047.
Lee, C. (2003). A scientometric study of the research performance of the Institute of Molecular and Cell Biology in Singapore. Scientometrics. 56(1): 95-110. https://doi.org/10.1023/A:1021902724734.
O’Farrell, P.H. (2014). Two-dimensional gel electrophoresis and the beginning of proteomics. Clinical Chemistry. 60(7): 1012-13. https://doi.org/10.1373/ clinchem.2014.221630. PMid: 24568796.
O’Farrell, P.Z., Goodman, H.M. and O’Farrell, P.H. (1977). High resolution two-dimensional electrophoresis of basic as well as acidic proteins. Cell. 12: 1133-41. https://doi.org/10.1016/0092-8674(77)90176-3.
Patra, S.K. and Bhattacharya, P. (2005). Bibliometric study of cancer research in India. DESIDOC Journal of Library and Information Technology. 25(2): 11-18. https://doi.org/10.14429/dbit.25.2.3650.
Patra, S.K. and Mishra, S. (2006). Bibliometric study of bioinformatics literature. Scientometrics. 67(3): 477-89. https://doi.org/10.1556/Scient.67.2006.3.9.
Price, D.J. (1986). Little science, big science... nd beyond. New York: Columbia University Press; p. 35-36.
Roy, S.B. (2019). Research output of biological science during 1901 1945: A scientometric analysis. DESIDOC Journal of Library ans Information Technology. 39(3): 96-103. https://doi.org/10.14429/djlit.39.3.14065.
Santha Kumar, R. and Kaliyaperumal, K. (2015). Scientometric analysis of global publication output in mobile technology. DESIDOC Journal of Library and Information Technology. 35(4): 287-92. https://doi.org/10.14429/djlit.35.4.7884.
Schubert, A. and Braun, T. (1986). Relative indicators and relational charts for comparative assessment of publication output and citation impact. Scientometrics. 9: 281-91. https://doi.org/10.1007/BF02017249.
Shao, H. et al. (2013). Analysis of oncology research from 2001 to 2010: A scientometric perspective. Oncology Reports. 29(4): 1441-52. https://doi.org/10.3892/ or.2013.2239. PMid: 23338281.
Sharifi, V. et al. (2008). Analysis of mental health research in the Islamic Republic of Iran over 3 decades: A scientometric study. Eastern Mediterranean Health Journal. 14(5): 1060-69.
Stanhill, G. (2001). The growth of climate change science: A scientometric study. Climatic Change. 48(2-3): 515-24. https://doi.org/10.1023/A:1010721600896.
Surwase, G., Kademani, B. S. and Kumar, V. (2008). Scientometric dimensions of pulsed laser deposition research: a global perspective, Annals of Library and Information Studies. 55(2): 101-10.
Swinbanks, D. (1995). Government backs proteome proposal. Nature. 378(6558): 653-53. https://doi.org/10.1038/378653a0. PMid: 7501000.
Teli, S. and Dutta, B. (2016). Study of citation distribution in astrophysics: An empirical approach. SRELS Journal of Information Management. 53(4): 255-69. https://doi.org/10.17821/srels/2016/v53i4/86579.
Teli, S. and Dutta, B. (2017). Scientometric study of superconductivity research in India from 1989 to 2014. SRELS Journal of Information Management. 54(5): 246-52 https://doi.org/10.17821/srels/2017/v54i5/115450.
Tripathi, K.K. (2000). Bioinformatics: the foundation of present and future biotechnology. Current Science. 79(5); 570-75.
Wasinger, V.C. et al. (1995). Progress with gene-product mapping of the Mollicutes: Mycoplasma Genitalium. Electrophoresis. 16(1): 1090-94. https://doi.org/10.1002/elps.11501601185. PMid: 7498152.
Wilkins, M. (2009). Proteomics data mining. Expert Review of Proteomics. 6(6):, 599-603. https:// doi.org/10.1586/epr.09.81. PMid: 19929606.
Downloads
Published
How to Cite
Issue
Section
License
All the articles published in Journal of Information and Knowledge are held by the Publisher. Sarada Ranganathan Endowment for Library Science (SRELS), as a publisher requires its authors to transfer the copyright prior to publication. This will permit SRELS to reproduce, publish, distribute and archive the article in print and electronic form and also to defend against any improper use of the article.
Accepted 2020-08-24
Published 2020-08-28
