Abstract
Facing the deluge of protein sequences generated in the post-genomic age, it is necessary to develop useful machine learning tools to predict the type of a hetero-oligomer. In this paper, a new method for the prediction of hetero-oligomeric protein types is proposed. Firstly, we constructed a high-quality benchmark data set. We collect as much desired information as possible, but meanwhile ensure a high quality for the working data sets, the data were screened strictly. Based on such a stringent data set, an effective sequence encoding scheme for truly representing the protein samples is used. Finally, a powerful prediction algorithm is introduced to identify the types of the given hetero-oligomers.
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© 2011 Springer-Verlag Berlin Heidelberg
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Wang, T., Hu, L., Wang, J. (2011). Application of NPE Algorithm in Prediction of Oligomeric Proteins. In: Lin, S., Huang, X. (eds) Advances in Computer Science, Environment, Ecoinformatics, and Education. CSEE 2011. Communications in Computer and Information Science, vol 217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23339-5_45
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DOI: https://doi.org/10.1007/978-3-642-23339-5_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23338-8
Online ISBN: 978-3-642-23339-5
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