Association algorithm to mine the rules that govern enzyme definition and to classify protein sequences |
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Authors: | Shih-Hau Chiu Chien-Chi Chen Gwo-Fang Yuan Thy-Hou Lin |
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Institution: | (1) Bioresource Collection and Research Center, Food Industry Research and Development Institute, HsinChu, Taiwan;(2) Institute of Molecular Medicine/Department of Life Science, National Tsing Hua University, HsinChu, Taiwan |
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Abstract: | Background The number of sequences compiled in many genome projects is growing exponentially, but most of them have not been characterized
experimentally. An automatic annotation scheme must be in an urgent need to reduce the gap between the amount of new sequences
produced and reliable functional annotation. This work proposes rules for automatically classifying the fungus genes. The
approach involves elucidating the enzyme classifying rule that is hidden in UniProt protein knowledgebase and then applying
it for classification. The association algorithm, Apriori, is utilized to mine the relationship between the enzyme class and significant InterPro entries. The candidate rules are
evaluated for their classificatory capacity. |
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Keywords: | |
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