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

2007

Talk

ei


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.
Year: 2007
Month: December
Day: 0

Department(s): Empirische Inferenz
Bibtex Type: Talk (talk)

Digital: 0
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

Links: Web

BibTex

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