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Empirical Inference Talk 2007

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

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Empirical Inference
Koji Tsuda
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Empirical Inference
Hiroto Saigo

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.

Author(s): Saigo, H. and Hattori, M. and Tsuda, K.
Links:
Year: 2007
Month: December
Day: 0
BibTeX Type: Talk (talk)
Digital: 0
Electronic Archiving: grant_archive
Event Name: NIPS 2007 Workshop on Machine Learning in Computational Biology
Event Place: Whistler, BC, Canada
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

BibTeX 

@talk{5012,
  title = {Reaction graph kernels for discovering missing enzymes in the plant secondary metabolism},
  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.},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = dec,
  year = {2007},
  author = {Saigo, H. and Hattori, M. and Tsuda, K.},
  month_numeric = {12}
}