首页> 外文OA文献 >Protein Sequence Motif Super-Rule-Tree (SRT) Structure Constructed by Hybrid Hierarchical K-means Clustering Algorithm

【2h】

Protein Sequence Motif Super-Rule-Tree (SRT) Structure Constructed by Hybrid Hierarchical K-means Clustering Algorithm

机译：混合层次K-均值聚类算法构建的蛋白质序列母题超规则树（SRT）结构

页面导航

著录项
引文网络
相似文献
相关主题

著录项

作者
Bernard Chen; Jieyue He; Steven Pellicer; Yi Pan;
展开▼
作者单位

展开▼
年度 2010
总页数
原文格式 PDF
正文语种
中图分类

相似文献

外文文献
中文文献
专利

1. Using Hybrid Hierarchical K-means (HHK) clustering algorithm for protein sequence motif Super-Rule-Tree (SRT) structure construction [J] . Chen B., He J., Pellicer S., International journal of data mining and bioinformatics . 2010,第3期

机译：使用混合层次K均值（HHK）聚类算法构建蛋白质序列基序超规则树（SRT）结构
2. Improved K-means clustering algorithm for exploring local protein sequence motifs representing common structural property [J] . Wei Zhong, Altun G., Harrison R., IEEE transactions on nanobioscience . 2005,第3期

机译：改进的K-means聚类算法，用于探索代表共同结构特性的局部蛋白质序列基序
3. Does Determination of Initial Cluster Centroids Improve the Performance of K-Means Clustering Algorithm? Comparison of Three Hybrid Methods by Genetic Algorithm, Minimum Spanning Tree, and Hierarchical Clustering in an Applied Study [J] . Saeedeh Pourahmad, Atefeh Basirat, Amir Rahimi, Computational and mathematical methods in medicine . 2020,第1期

机译：初始簇质心的确定是否提高了K-Means聚类算法的性能？应用研究中遗传算法，最小生成树和分层聚类的三种混合方法的比较
4. Protein Sequence Motif Super-Rule-Tree (SRT) Structure Constructed by Hybrid Hierarchical K-Means Clustering Algorithm [C] . IEEE International Conference on Bioinformatics and Biomedicine . 2008

机译：由混合分层K-Means聚类算法构建的蛋白质序列基序超规则树（SRT）结构
5. Protein structure analysis and prediction utilizing the Fuzzy Greedy K-means Decision Forest model and Hierarchically-Clustered Hidden Markov Models method. [D] . Hudson, Cody Landon. 2013

机译：利用模糊贪婪K均值决策森林模型和层次聚类的隐马尔可夫模型方法对蛋白质结构进行分析和预测。
6. Does Determination of Initial Cluster Centroids Improve the Performance of K-Means Clustering Algorithm? Comparison of Three Hybrid Methods by Genetic Algorithm Minimum Spanning Tree and Hierarchical Clustering in an Applied Study [O] . Saeedeh Pourahmad, Atefeh Basirat, Amir Rahimi, 2020

机译：初始簇质心的确定是否提高了K-Means聚类算法的性能？应用研究中遗传算法最小生成树和分层聚类的三种混合方法的比较
7. Does Determination of Initial Cluster Centroids Improve the Performance of K-Means Clustering Algorithm? Comparison of Three Hybrid Methods by Genetic Algorithm, Minimum Spanning Tree, and Hierarchical Clustering in an Applied Study [O] . Saeedeh Pourahmad, Atefeh Basirat, Amir Rahimi, 2020

机译：初始簇质心的确定是否提高了K-Means聚类算法的性能？应用研究中遗传算法，最小生成树和分层聚类的三种混合方法的比较

Protein Sequence Motif Super-Rule-Tree (SRT) Structure Constructed by Hybrid Hierarchical K-means Clustering Algorithm

著录项

引文网络

相似文献

相关主题

期刊订阅