Prediction of xylanase optimal temperature by support vector regression
Background: Support vector machine (SVM), a novel powerful machine learning technology, was used to develop the non-linear quantitative structure-property relationship (QSPR) model of the G/11 xylanase based on the amino acid composition. The uniform design (UD) method was applied to optimize the ru...
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| Auteurs principaux: | , |
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| Langue: | English |
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Pontificia Universidad Católica de Valparaíso
2012
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| Accès en ligne: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-34582012000100007 |
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