TY - GEN
T1 - Towards automatic extraction of social networks of organizations in pub-med abstracts
AU - Jonnalagadda, Siddhartha
AU - Topham, Philip
AU - Gonzalez, Graciela
PY - 2009
Y1 - 2009
N2 - Social Network Analysis (SNA) of organizations can attract great interest from government agencies and scientists for its ability to boost translational research and accelerate the process of converting research to care. For SNA of a particular disease area, we need to identify the key research groups in that area by mining the affiliation information from PubMed. This not only involves recognizing the organization names in the affiliation string, but also resolving ambiguities to identify the article with a unique organization. We present here a process of normalization that involves clustering based on local sequence alignment metrics and local learning based on finding connected components. We demonstrate the application of the method by analyzing organizations involved in angiogenensis treatment, and demonstrating the utility of the results for researchers in the pharmaceutical and biotechnology industries or national funding agencies.
AB - Social Network Analysis (SNA) of organizations can attract great interest from government agencies and scientists for its ability to boost translational research and accelerate the process of converting research to care. For SNA of a particular disease area, we need to identify the key research groups in that area by mining the affiliation information from PubMed. This not only involves recognizing the organization names in the affiliation string, but also resolving ambiguities to identify the article with a unique organization. We present here a process of normalization that involves clustering based on local sequence alignment metrics and local learning based on finding connected components. We demonstrate the application of the method by analyzing organizations involved in angiogenensis treatment, and demonstrating the utility of the results for researchers in the pharmaceutical and biotechnology industries or national funding agencies.
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U2 - 10.1109/BIBMW.2009.5332108
DO - 10.1109/BIBMW.2009.5332108
M3 - Conference contribution
AN - SCOPUS:72949087375
SN - 9781424451210
T3 - Proceedings - 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009
SP - 279
EP - 286
BT - Proceedings - 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009
T2 - 2009 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2009
Y2 - 1 November 2009 through 4 November 2009
ER -