Abstract
133,251 terms extracted from biological books and dictionaries were processed to automatically extract semantic relations among terms such as hierarichical and equivalent relations. Extracted terms represent biological concept, thus extracted relations define the biological conceptual network. Analysis of the constructed conceptual network shows double scale-free property, and concepts with large number of semantic relations are shown to be important biological concepts. These concepts with large number of semantic relations shorten the time to search concepts in the network.
