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Scientific Collaboration Networks Using Biomedical Text

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Biomedical Literature Mining

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1159))

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Abstract

The combination of scientific knowledge and experience is the key success for biomedical research. This chapter demonstrates some of the strategies used to help in identifying key opinion leaders with the expertise you need, thus enabling an effort to increase collaborative biomedical research.

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References

  1. Balas EA, Boren SA (2000) Managing clinical knowledge for health care improvement. Yearb Med Inform 65–70

    Google Scholar 

  2. Nair HS, Manchanda P, Bhatia T (2010) Asymmetric social interactions in physician prescription behavior: the role of opinion leaders. J Market Res 47(5):883–895

    Article  Google Scholar 

  3. Valente TW, Pumpuang P (2006) Identifying opinion leaders to promote behavior change. Health Educ Behav 34(6):881–896

    Article  Google Scholar 

  4. Bales M, Johnson SB, Weng C (2008) Social network analysis of interdisciplinarity in obesity research. AMIA Annu Symp Proc 870

    Google Scholar 

  5. Merrill J, Hripcsak G (2008) Using social network analysis within a department of biomedical informatics to induce a discussion of academic communities of practice. J Am Med Informat Assoc 15(6):780–782

    Article  Google Scholar 

  6. Bordea G (2010) Concept extraction applied to the task of expert finding. In: Aroyo L, Antoniou G, Hyvönen E, Teije A, Stuckenschmidt H, Cabral L, Tudorache T (eds) The semantic web: research and applications, vol 6089. Springer, Berlin, pp 451–456

    Chapter  Google Scholar 

  7. Buitelaar P, Eigner T (2009) Expertise mining from scientific literature In: Proceedings of the fifth international conference on knowledge capture. ACM, New York, NY, USA, pp 171–172

    Google Scholar 

  8. Christakis NA, Fowler JH (2007) The spread of obesity in a large social network over 32 years. [Research Support, N.I.H., Extramural]. N Engl J Med 357(4):370–379. doi:10.1056/NEJMsa066082

    Article  CAS  PubMed  Google Scholar 

  9. Borthakur D (2007) The hadoop distributed file system: architecture and design. http://hadoop.apache.org

  10. Jonnalagadda S, Peeler R, Topham P (2012) Discovering opinion leaders for medical topics using news articles. J Biomed Semantics 3(1):2. doi:10.1186/2041-1480-3-2

    Article  PubMed Central  PubMed  Google Scholar 

  11. Jonnalagadda SR, Topham P (2010) NEMO: extraction and normalization of organization names from PubMed affiliations. J Biomed Discov Collab 5:50–75

    PubMed Central  PubMed  Google Scholar 

  12. Lnx-Pharma (2007) Using large scale social network analysis—a comparative analysis for finding key opinion leaders. http://www.lnxpharma.com/Whitepapers/Lnx_Whitepaper_2.pdf

  13. Bastian M, Heymann S, Jacomy M (2009) Gephi: an open source software for exploring and manipulating networks. Paper presented at the international AAAI conference on weblogs and social media

    Google Scholar 

  14. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  15. Handcock MS, Hunter DR, Butts CT, Goodreau SM, Morris M (2008) Statnet: software tools for the representation, visualization, analysis and simulation of network data. J Stat Softw 24(1):1548

    Google Scholar 

  16. NLM (2013) PubMed interface. http://www.ncbi.nlm.nih.gov/pubmed

  17. Li YN, Wang YP, Du JT (2013) E-FFC: an enhanced form-focused crawler for domain-specific deep web databases. J Intell Inf Syst 40(1):159–184. doi:10.1007/s10844-012-0221-8

    Article  Google Scholar 

  18. Boldi P, Codenotti B, Santini M, Vigna S (2004) UbiCrawler: a scalable fully distributed Web crawler. Software Pract Ex 34(8):711–726. doi:10.1002/Spe.587

    Article  Google Scholar 

  19. McCallum AK (2002) MALLET: a machine learning for language toolkit. http://mallet.cs.umass.edu

  20. Torvik VI, Smalheiser NR (2009) Author name disambiguation in MEDLINE. ACM Trans Knowl Discov Data 3(3)

    Google Scholar 

  21. Fraley C, Raftery AE (2002) Model-based clustering, discriminant analysis, and density estimation. J Am Stat Assoc 97(458):611–631

    Article  Google Scholar 

  22. Kriegel H-P, Kröger P, Zimek A (2009) Clustering high-dimensional data: a survey on subspace clustering, pattern-based clustering, and correlation clustering. ACM Trans Knowl Discov Data 3(1):1

    Article  Google Scholar 

  23. Hanneman RA, Riddle M (eds) (2005) Introduction to social network methods. University of California, Riverside, Riverside, CA

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Preventive Medicine, Health and Biomedical Informatics, 750 N Lake Shore, Floor 11, Chicago, IL, 60611, USA

    Siddhartha R. Jonnalagadda

  2. BizKnowlogy, Huntington Beach, CA, 92605, USA

    Philip S. Topham, Edward J. Silverman & Ryan G. Peeler

  3. Lnx Research LLC, Garden Grove, CA, USA

    Philip S. Topham, Edward J. Silverman & Ryan G. Peeler

Authors
  1. Siddhartha R. Jonnalagadda
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  2. Philip S. Topham
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  3. Edward J. Silverman
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  4. Ryan G. Peeler
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Corresponding author

Correspondence to Siddhartha R. Jonnalagadda .

Editor information

Editors and Affiliations

  1. GlaxoSmithKline, King of Prussia, Pennsylvania, USA

    Vinod D. Kumar

  2. GlaxoSmithKline, Hitchin, Hertfordshire, United Kingdom

    Hannah Jane Tipney

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© 2014 Springer Science+Business Media New York

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Jonnalagadda, S.R., Topham, P.S., Silverman, E.J., Peeler, R.G. (2014). Scientific Collaboration Networks Using Biomedical Text. In: Kumar, V., Tipney, H. (eds) Biomedical Literature Mining. Methods in Molecular Biology, vol 1159. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-0709-0_9

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  • DOI: https://doi.org/10.1007/978-1-4939-0709-0_9

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-0708-3

  • Online ISBN: 978-1-4939-0709-0

  • eBook Packages: Springer Protocols

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