Prediction of protein secondary structures of all types using new hypersphere machine learning method

Markku Siermala

Conference Proceedings

Prediction of protein secondary structures of all types using new hypersphere machine learning method

Siermala M

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2001) 2101 117-120

DOI: 10.1007/3-540-48229-6_16

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Abstract

In this paper, we present a new hypersphere machine learning method and use it to predict all protein secondary structures. It finds sequences with sufficiently high homology. Prediction accuracy of the new method with protein secondary structures was good (average 89.3%). However, the method could not classify all test cases.

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Siermala, M. (2001). Prediction of protein secondary structures of all types using new hypersphere machine learning method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2101, pp. 117–120). Springer Verlag. https://doi.org/10.1007/3-540-48229-6_16

Prediction of protein secondary structures of all types using new hypersphere machine learning method

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