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Prediction of Small Molecules' Metabolic Pathways Based on Functional Group Composition

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Abstract:

How to correctly and efficiently determine small molecules' biological function is a challenge and has a positive effect on further metabonomics analysis. Here, we introduce a computational approach to address this problem. The new approach is based on AdaBoost method and featured by function group composition to the metabolic pathway analysis, which can fast and automatically map the small chemical molecules back to the possible metabolic pathway that they belong to. As a result, jackknife cross validation test and independent set test on the model reached 73.7% and 73.8%, respectively. It can be concluded that the current approach is very promising for mapping some unknown molecules' possible metabolic pathway. An online predictor developed by this research is available at http://chemdata.shu.edu.cn/pathway.





Keywords: Adaboost; Independent set test; Jackknife cross-validation test; Metabolism

Document Type: Research Article

DOI: http://dx.doi.org/10.2174/092986609788923374

Publication date: August 1, 2009

More about this publication?
  • Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.
ben/ppl/2009/00000016/00000008/art00015
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