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  Reaction graph kernels for discovering missing enzymes in the plant secondary metabolism

Saigo, H., Hattori, M., & Tsuda, K. (2007). Reaction graph kernels for discovering missing enzymes in the plant secondary metabolism. Talk presented at NIPS 2007 Workshop on Machine Learning in Computational Biology (MLCB 2007). Whistler, BC, Canada. 2007-12-07 - 2007-12-08.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-CAFF-8 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-447C-5
Genre: Talk

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 Creators:
Saigo, H1, 2, Author              
Hattori, M, Author
Tsuda, K1, 2, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Secondary metabolic pathway in plant is important for finding druggable candidate enzymes. However, there are many enzymes whose functions are still undiscovered especially in organism-specific metabolic pathways. We propose reaction graph kernels for automatically assigning the EC numbers to unknown enzymatic reactions in a metabolic network. Experiments are carried out on KEGG/REACTION database and our method successfully predicted the first three digits of the EC number with 83 accuracy.We also exhaustively predicted missing enzymatic functions in the plant secondary metabolism pathways, and evaluated our results in biochemical validity.

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 Dates: 2007-12
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 5012
 Degree: -

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Title: NIPS 2007 Workshop on Machine Learning in Computational Biology (MLCB 2007)
Place of Event: Whistler, BC, Canada
Start-/End Date: 2007-12-07 - 2007-12-08
Invited: Yes

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