Abstract
Transmembrane proteins are the primary targets for the development of new drugs, and a number of algorithms that predict transmembrane topology are publicly available on the Web. In this paper, we present a novel approach using both SVM and HMM methods and we demonstrate that our system outperform the previous systems which only use either HMM methods or SVM methods alone.
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Kim, M.K., Song, C.H., Yoo, S.J., Lee, S.H., Park, H.S. (2005). A Hybrid Approach to Combine HMM and SVM Methods for the Prediction of the Transmembrane Spanning Region. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553939_112
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DOI: https://doi.org/10.1007/11553939_112
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28896-1
Online ISBN: 978-3-540-31990-0
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