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Prediction of solubility of lysozyme in lysozyme-NaCl-H2O system with artificial neural network
Alternative TitleJ. Cryst. Growth
Zhang, XP; Zhang, SJ; He, XZ
2004-03-15
Source PublicationJOURNAL OF CRYSTAL GROWTH
ISSN0022-0248
Volume264Issue:1-3Pages:409-416
AbstractModeling and prediction of protein solubility is a key to developing the protein crystal growth and crystallization process. In this paper a back propagation network was used for predicting the solubility of protein in lysozyme-NaCl-H2O system. It was found that properly selected and trained neural network could fairly represent the dependence of protein solubility on the pH, salt concentration, and temperature. The RMSD (root mean square deviation) for prediction of the solubility of lysozyme in lysozyme-NaCl-H2O system was 0.07% by the artificial neural network (ANN) method, which is better than that of with thermodynamic models. The ANNs have been proven to be an effective tool for correlation and prediction of protein solubility in protein-salt-water system. (C) 2003 Elsevier B.V. All rights reserved.; Modeling and prediction of protein solubility is a key to developing the protein crystal growth and crystallization process. In this paper a back propagation network was used for predicting the solubility of protein in lysozyme-NaCl-H2O system. It was found that properly selected and trained neural network could fairly represent the dependence of protein solubility on the pH, salt concentration, and temperature. The RMSD (root mean square deviation) for prediction of the solubility of lysozyme in lysozyme-NaCl-H2O system was 0.07% by the artificial neural network (ANN) method, which is better than that of with thermodynamic models. The ANNs have been proven to be an effective tool for correlation and prediction of protein solubility in protein-salt-water system. (C) 2003 Elsevier B.V. All rights reserved.
KeywordPrediction Solubility Artificial Neural Network Lysozyme Protein
SubtypeArticle
WOS HeadingsScience & Technology ; Physical Sciences ; Technology
DOI10.1016/j.jcrysgro.2003.12.038
URL查看原文
Indexed BySCI
Language英语
WOS KeywordEGG-WHITE LYSOZYME ; VAPOR-LIQUID-EQUILIBRIUM
WOS Research AreaCrystallography ; Materials Science ; Physics
WOS SubjectCrystallography ; Materials Science, Multidisciplinary ; Physics, Applied
WOS IDWOS:000220345400064
Citation statistics
Cited Times:24[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Version出版稿
Identifierhttp://ir.ipe.ac.cn/handle/122111/4988
Collection研究所(批量导入)
AffiliationChinese Acad Sci, Inst Proc Engn, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Zhang, XP,Zhang, SJ,He, XZ. Prediction of solubility of lysozyme in lysozyme-NaCl-H2O system with artificial neural network[J]. JOURNAL OF CRYSTAL GROWTH,2004,264(1-3):409-416.
APA Zhang, XP,Zhang, SJ,&He, XZ.(2004).Prediction of solubility of lysozyme in lysozyme-NaCl-H2O system with artificial neural network.JOURNAL OF CRYSTAL GROWTH,264(1-3),409-416.
MLA Zhang, XP,et al."Prediction of solubility of lysozyme in lysozyme-NaCl-H2O system with artificial neural network".JOURNAL OF CRYSTAL GROWTH 264.1-3(2004):409-416.
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