Biomedical Literature Mining with Transitive Closure and Maximum Network Flow

Biomedical Literature Mining with Transitive Closure and Maximum Network Flow

This thesis examines biomedical text mining with an application in bone biology. A special thanks is extended to Anita Park and Mark Jaeger from the Purdue University Graduate School Office, who acted as invaluable assets in the formatting of the thesis. IUPUI and every other university would be fo...

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Bibliographic Details
Main Author: Hoblitzell, Andrew P.
Other Authors: Mukhopadhyay, Snehasis
Language:en_US
Published: http://doi.acm.org/10.1145/1851476.1851552 2011
Subjects:
Biomedical text mining
Bioinformatics
Hypergraphs
Information storage and retrieval systems > Biology
Data mining
Biological literature
Online Access:Andrew Hoblitzell, Snehasis Mukhopadhyay, Qian You, Shiaofen Fang, Yuni Xia, and Joseph Bidwell. 2010. Text mining for bone biology. In Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing (HPDC '10). ACM, New York, NY, USA, 522-530. DOI=10.1145/1851476.1851552 http://doi.acm.org/10.1145/1851476.1851552
http://hdl.handle.net/1805/2609

Internet

Andrew Hoblitzell, Snehasis Mukhopadhyay, Qian You, Shiaofen Fang, Yuni Xia, and Joseph Bidwell. 2010. Text mining for bone biology. In Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing (HPDC '10). ACM, New York, NY, USA, 522-530. DOI=10.1145/1851476.1851552 http://doi.acm.org/10.1145/1851476.1851552
http://hdl.handle.net/1805/2609

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