A Little Semantic Web Goes a Long Way in Biology
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@INPROCEEDINGS{Wolstencroft2005a, author = {Wolstencroft, Katherine and Brass, Andrew and Horrocks, Ian and Lord, Phillip and Sattler, Ulrike and Turi, Daniele and Stevens, Robert}, title = {A Little Semantic Web Goes a Long Way in Biology}, booktitle = {International Semantic Web Conference}, year = {2005}, pages = {786-800}, month = {October}, publisher = {Springer Berlin / Heidelberg}, abstract = {We show how state-of-the-art Semantic Web technology can be used in e-Science, in particular, to automate the classification of proteins in biology. We show that the resulting classification was of comparable quality to that performed by a human expert, and how investigations using the classified data even resulted in the discovery of significant information that had previously been overlooked, leading to the identification of a possible drug-target.}, doi = {10.1007/11574620_56}, owner = {alanrw}, timestamp = {2008.06.02} }
Citation: K. Wolstencroft, A. Brass, I. Horrocks, P. Lord, U. Sattler, D. Turi, and R. Stevens, "A Little Semantic Web Goes a Long Way in Biology," in International Semantic Web Conference, 2005, pp. 786-800.
Abstract
We show how state-of-the-art Semantic Web technology can be used in e-Science, in particular, to automate the classification of proteins in biology. We show that the resulting classification was of comparable quality to that performed by a human expert, and how investigations using the classified data even resulted in the discovery of significant information that had previously been overlooked, leading to the identification of a possible drug-target.
