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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Wolstencroft, K., Brass, A., Horrocks, I., Lord, P., Sattler, U., Turi, D., & Stevens, R. (2005). A little semantic web goes a long way in biology. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3729 LNCS, pp. 786–800). https://doi.org/10.1007/11574620_56
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