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231223s2009 xx |||||o 00| ||eng c |
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7 |
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|a 10.1002/jcc.21115
|2 doi
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|a pubmed24n0615.xml
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|a (DE-627)NLM184497132
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|a (NLM)19009604
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|a DE-627
|b ger
|c DE-627
|e rakwb
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| 041 |
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|a eng
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| 100 |
1 |
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|a Qiu, Jian-Ding
|e verfasserin
|4 aut
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| 245 |
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|a Using support vector machines for prediction of protein structural classes based on discrete wavelet transform
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|c 2009
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Completed 14.07.2009
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|a Date Revised 18.11.2010
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|a published: Print
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|a Citation Status MEDLINE
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|a 2008 Wiley Periodicals, Inc.
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|a The prediction of secondary structure is a fundamental and important component in the analytical study of protein structure and functions. How to improve the predictive accuracy of protein structural classification by effectively incorporating the sequence-order effects is an important and challenging problem. In this study, a new method, in which the support vector machine combines with discrete wavelet transform, is developed to predict the protein structural classes. Its performance is assessed by cross-validation tests. The predicted results show that the proposed approach can remarkably improve the success rates, and might become a useful tool for predicting the other attributes of proteins as well
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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| 650 |
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|a Proteins
|2 NLM
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| 700 |
1 |
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|a Luo, San-Hua
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Huang, Jian-Hua
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Liang, Ru-Ping
|e verfasserin
|4 aut
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| 773 |
0 |
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|i Enthalten in
|t Journal of computational chemistry
|d 1984
|g 30(2009), 8 vom: 20. Juni, Seite 1344-50
|w (DE-627)NLM098138448
|x 1096-987X
|7 nnns
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| 773 |
1 |
8 |
|g volume:30
|g year:2009
|g number:8
|g day:20
|g month:06
|g pages:1344-50
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| 856 |
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|u http://dx.doi.org/10.1002/jcc.21115
|3 Volltext
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| 952 |
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|d 30
|j 2009
|e 8
|b 20
|c 06
|h 1344-50
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