Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Xiuzhen Hu

Showing results (1-10 of 30) with videos related to

Pageof 3
Sort By:
Asian Journal of Surgery|April 28, 2023
Application of a quality management model in the clinical laboratory for reporting of the critical valuesXiuzhen Hu
Protein and Peptide Letters|August 4, 2009
Predicting enzyme subclasses by using support vector machine with composite vectorsRuijia Shi, Xiuzhen Hu
Journal of Computational Chemistry|April 25, 2008
Using support vector machine to predict beta- and gamma-turns in proteinsXiuzhen Hu, Qianzhong Li
Biomed Research International|August 20, 2014
Recognition of 27-class protein folds by adding the interaction of segments and motif informationZhenxing Feng, Xiuzhen Hu
Protein and Peptide Letters|October 6, 2009
The recognition of 27-class protein folds: approached by increment of diversity based on multi-characteristic parametersHuaiguang Zhang, Xiuzhen Hu, Qianzhong Li
BMC Bioinformatics|November 19, 2016
Protein ligand-specific binding residue predictions by an ensemble classifierXiuzhen Hu, Kai Wang, Qiwen Dong
Journal of Computational Chemistry|October 24, 2019
Recognizing five molecular ligand-binding sites with similar chemical structureXiuzhen Hu, Riletu Ge, Zhenxing Feng
Journal of Theoretical Biology|July 26, 2011
Prediction of β-turn types in protein by using composite vectorXiaobo Shi, Xiuzhen Hu, Shaobo Li, et al.
IEEE Transactions on Computational Biology and Bioinformatics|December 17, 2025
SG-DCNN: A Deep Learning Method Integrating Self-Attention Mechanism and Generative Adversarial Network for Predicting Ion-Ligand Binding Residues in Small SamplesBenjun Tang, Xiuzhen Hu, Yuqian Yao, et al.
Bioinformatics (Oxford, England)|July 6, 2016
Recognizing metal and acid radical ion-binding sites by integrating ab initio modeling with template-based transferalsXiuzhen Hu, Qiwen Dong, Jianyi Yang, et al.
Pageof 3

Showing results (1-10 of 30) with videos related to

Sort By:
Pageof 3
Asian Journal of Surgery|April 28, 2023
Application of a quality management model in the clinical laboratory for reporting of the critical valuesXiuzhen Hu
Protein and Peptide Letters|August 4, 2009
Predicting enzyme subclasses by using support vector machine with composite vectorsRuijia Shi, Xiuzhen Hu
Journal of Computational Chemistry|April 25, 2008
Using support vector machine to predict beta- and gamma-turns in proteinsXiuzhen Hu, Qianzhong Li
Biomed Research International|August 20, 2014
Recognition of 27-class protein folds by adding the interaction of segments and motif informationZhenxing Feng, Xiuzhen Hu
Protein and Peptide Letters|October 6, 2009
The recognition of 27-class protein folds: approached by increment of diversity based on multi-characteristic parametersHuaiguang Zhang, Xiuzhen Hu, Qianzhong Li
BMC Bioinformatics|November 19, 2016
Protein ligand-specific binding residue predictions by an ensemble classifierXiuzhen Hu, Kai Wang, Qiwen Dong
Journal of Computational Chemistry|October 24, 2019
Recognizing five molecular ligand-binding sites with similar chemical structureXiuzhen Hu, Riletu Ge, Zhenxing Feng
Journal of Theoretical Biology|July 26, 2011
Prediction of β-turn types in protein by using composite vectorXiaobo Shi, Xiuzhen Hu, Shaobo Li, et al.
IEEE Transactions on Computational Biology and Bioinformatics|December 17, 2025
SG-DCNN: A Deep Learning Method Integrating Self-Attention Mechanism and Generative Adversarial Network for Predicting Ion-Ligand Binding Residues in Small SamplesBenjun Tang, Xiuzhen Hu, Yuqian Yao, et al.
Bioinformatics (Oxford, England)|July 6, 2016
Recognizing metal and acid radical ion-binding sites by integrating ab initio modeling with template-based transferalsXiuzhen Hu, Qiwen Dong, Jianyi Yang, et al.
Pageof 3