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2010, Number 2

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Rev Cub Gen 2010; 4 (2)

Pubmed as a source for bibliometric studies in Medical Genetics in Cuba

Soriano-Torres M, Arencibia-Jorge R

Language: Spanish
References: 45
Page: 5-11
PDF size: 334.26 Kb.


ABSTRACT

Bibliometrics is a discipline where statistical and mathematical methods are applied to written sources of information, mainly to specialized literature, in order to obtain not unexplicit information highly valuable value for decision makers at an institutional level. In the current work, the usefulness of Pubmed for bibliometric studies in the field of Medical Genetics in Cuba is evaluated, and some difficulties related to the lack of standardization in the author and institution fields are mentioned. In order to analyze these items in a particular study, the manual or semiautomatic review of theses fields is suggested. Finally, some tools developed for the performance of bibliometric studies using Pubmed, as GoPubmed and PubmedPubReMiner, are mentioned.


REFERENCES

  1. Pritchard, A. Statistical bibliography or bibliometrics? Journal of Documentation. 1969;25(4):348-9.

  2. Camps D. Limitaciones de los indicadores bibliométricos en la evaluación de la actividad científica biomédica. Colombia Médica. 2008;39(1):74-9.

  3. Callon M.N., Courtial J.P, Laville FN. Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry. Scientometrics. 1991;22(1):155-205.

  4. He Q. Knowledge Discovery through Co-Word Analysis. Library Trends. 1999;48:133-59.

  5. Leydesdorff, Loet. Why words and co-words cannot map the development of the sciences. Journal of the American Society for Information Science. 1997;48(5):418-27.

  6. Peters, H.P, van Raan A.F. Co-word-based science maps of chemical engineering. Part I: Representations by direct multidimensional scaling. Research Policy. 1993;22(1):23.

  7. Michalopoulos A, Falagas ME. A bibliometric analysis of global research production in respiratory medicine.Chest. 2005;128(6):3993–8.

  8. Rahman M, Haque TL, Fukui T. Research articles published in clinical radiology journals: trend of contribution from different countries. Acad Radiol. 2005;12(7):825–9.

  9. Falagas ME, Karavasiou AI, Bliziotis IA. Estimates of global research productivity in virology. J Med Virol. 2005;76(2):229–33.

  10. Cimmino MA, Maio T, Ugolini D, Borasi F, Mela GS. Trends in otolaryngology research during the period 1995–2000: a bibliometric approach. Otolaryngol Head Neck Surg. 2005;132(2):295–302.

  11. Ugolini D, Mela GS. Oncological research overview in the European Union. A 5-year survey. Eur J Cancer. 2003;39(13):1888–94.

  12. Grossi F, Belvedere O, Rosso R. Geography of clinical cancer research publications from 1995 to 1999. Eur J Cancer. 2003;39(1):106–11.

  13. Ugolini D, Cimmino MA, Casilli C, Mela GS. How the European Union writes about ophthalmology. Scientometrics. 2001;52:45–58.

  14. Mela GS, Cimmino MA. An overview of rheumatological research in the European Union. Ann Rheum Dis. 1998;57:643–7.

  15. Ferguson-Smith, M.A. Cytogenetics and the evolution of medical genetics. American College of Medical Genetics. 2008;10(8):1-7.

  16. Callon M.N, Courtial J.P, Laville F.N. Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry. Scientometrics. 1991;22(1):155-205.

  17. van Raan A.F, Tijssen R.J. The neural net of neural network research. Scientometrics. 1993;26(1):169-192.

  18. Callon M, Law J, Rip A. Mapping the Dynamics of Science and Technology: The Sociology of an Actor-Network: The Case of the Electric Vehicle. London: Macmillan; 1986.

  19. Callon M, Law J, Rip A. Mapping the Dynamics of Science and Technology: Sociology of Science in the Real World. London: Macmillan; 1986.

  20. Ding Y., Chowdhury G.G, Foo S. Bibliometric cartography of information retrieval research by using co-word analysis. Information Processing and Management. 2001;37(6):817-42.

  21. Garfield, E. Scientography: Mapping the Tracks of Science. Current Contents: Social and Behavioral Sciences. 1994;7(45):5-10.

  22. Healey, Peter, Harry Rothman, and Paul K. Hoch. An experimental in science mapping for research planning. Research Policy. 1986;15(5):233.

  23. Moed HF. Citation analysis in research evaluation. Berlin: Springer; 2005.

  24. Ugolini D, Puntoni R, Perera F.P, Schulte P, Bonsái S. A bibliometric analysis of scientific production in cancer molecular epidemiology. Carcinogenesis. 2007;28 (8):1774-9.

  25. van Raan, A.F. Scientometrics: State-of-the-art. Scientometrics. 1997;38(1):205-218.

  26. Dalpe, R. Bibliometric Analysis of Biotechnology. Scientometrics. 2002;55(2):189-213.

  27. PubMed Overview [en línea] 2006, June 30, [fecha de acceso20 de septiembre de 2006] URL disponible en: http:// www.ncbi.nlm.nih.gov/entrez/query/static/overview.html

  28. Maksim V Plikus, Zina Zhang y Cheng-Ming Chuong. PubFocus:semantic MEDLINE/PubMed citations analytics through integration of controlled biomedical dictionaries and ranking algorithm. BMC Bioinformatics. 2006;7:424.

  29. National Library of Medicine, Bethesda, MD, USA. 2005. Pubmed manual. Available at: http://www.nlm.nih.gov/ pubs/manuals/pubmed.pdf

  30. Hersh WR, Buckley C, Leone TJ, Hickam DH: OHSUMED: an interactive retrieval evaluation and new large test collection for research. Croft WB and vanRijsbergen CJ: Springer-Verlag; 1994.

  31. Srinivasan P. Optimal document-indexing vocabulary for Medline. Information Processing & Management. 1996; 32(5), 503-514.

  32. Savoy, J. Bibliographic database access using free-text and controlled vocabulary: An evaluation. Information Processing & Management. 2005;41(4):873–890.

  33. Abdou, S y J. Savoy. Searching in MEDLINE: Query expansion and manual indexing evaluation. Information Processing and management. 2008;44:781-9.

  34. Royer L, Plake C, Schroeder M. Procedures of the German Conference on Bioinformatics: Identification of cancer and cell-cycle genes with protein interactions and literature mining. Halle: Germany; 2009.

  35. Kovic I. GoPubMed. [en línea] [fecha de acceso 1 de agosto de 2008]. URL disponible en : http://ivor-kovic. com/blog/?p=128

  36. Cañedo Andalia R, Santana Arroyo S, Santovenia Díaz J. GoPubMed y PubMedReMiner: dos herramientas para los análisis métricos y el descubrimiento de conocimientos en PubMed. Acimed. 2008;18(3). URL disponible en: www. bvs.sld.cu/revistas/aci/vol18_3_08/aci07908.pdf

  37. Kovic I. PubReMiner. [en línea] [fecha de acceso 29 de julio de 2008] URL disponible en: http://ivor-kovic.com/ blog/?p=89

  38. Siadaty MS, Shu J, Knaus WA. Relemed: sentence-level search engine with relevance score for the MEDLINE database of biomedical articles. BMC Med Inform Decis Mak. 2007;10(7):1.

  39. Sellen MK. Bibliometrics: An annotated bibliography, 1970-1990. New Cork: GK Hall & Co; 1993.

  40. White, H.D. & McCain, K.W. Bibliometrics. Annual Review of Information Science and Technology.1989;24: 119-185.

  41. White, H.D. & McCain, K.W. Visualization of literatures. Annual Review of Information Science and Technology. 1997;32:99-168.

  42. Leydesdorff, Loet. Words and co-words as indicators of intellectual organization. Research Policy. 1989;18(4): 209-223.

  43. Horrobin, D.F. The philosophical basis of peer review and the suppression innovation. Journal of the American Medica Association (JAMA). 1990;263:1438-1441.

  44. Moxham, H.; Anderson J. Peer review. A view from the inside. Science and Technology Policy. 1992:7-15.

  45. Rinia, E.J.; Leeuwen, Th.N. van; Vuren, H.G. van; Raan, A.F.J. van. Comparative analysis of the set of bibliometric indicators and central peer review criteria. Evaluation of condensed matter physics in the Netherlands. Reseach Policy. 1998;27: 95-107.




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