Book ChapterDOI
Review of Clustering Methods: Toward Phylogenetic Tree Constructions
Akansha Sharma,Shailesh Jaloree,Ramjeevan Singh Thakur +2 more
- pp 475-480
TLDR
The current text makes us informative about clustering methods used to generate phylogenetic trees by both distance- and character-based analyses.Abstract:
In modern context, integrated approach of science and technology has given new subjects such as bioinformatics. This discipline of informatics gave a pathway to understand the larger data of various biological systems in much simplified manner. The various attributes studied in the form of computational patterns result in phylogenetic tree construction. These phylogenetic trees establish both similarities and dissimilarities among organisms. Different algorithms of clustering were studied and compared on various parameters to establish the best among them and utilities of others methods as well. The current text makes us informative about clustering methods used to generate phylogenetic trees by both distance- and character-based analyses.read more
Citations
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Journal ArticleDOI
Research on clustering analysis of Internet public opinion
TL;DR: Experimental results show that the proposed similarity analysis methods can quickly obtain the Internet public opinion, and has high accuracy rate of clustering, which provide an important technical support for Internet public public opinion monitoring and recognizing.
Proceedings ArticleDOI
Fuzzy clustering based on re-classification of border data for incomplete dataset
TL;DR: The proposed algorithm focuses on the re-classification of “suspected misclassified” border data (abbreviated as SM border data) and outperforms the classical FCM-based algorithms for incomplete data.
Posted ContentDOI
Clustering analysis of single nucleotide polymorphism data reveals population structure of SARS-CoV-2 worldwide
Yawei Li,Qingyun Liu,Yuan Luo +2 more
TL;DR: The identification of the mutations that are strongly associated with clusters have potential implications for diagnosis and pathogenesis of COVID-19 and will enable further study of variant population structures in specific regions of these fast-growing viruses.
Posted ContentDOI
Unsupervised clustering analysis reveals global population structure of SARS-CoV-2
TL;DR: This study provides a concrete framework for the use of clustering methods in phylogenetic analysis to study the global population structure of SARS-CoV-2 and indicated that genetic factors and human migration played an important role in shaping the specific geographical distribution of population structure.
Journal ArticleDOI
Unsupervised clustering of SARS-CoV-2 using deep convolutional autoencoder
Fayroz F. Sherif,Khaled S. Ahmed +1 more
TL;DR: In this article , the authors used deep learning to identify the main clusters of SARS-CoV-2 population structure based on convolutional autoencoder (CAE) trained with numerical feature vectors mapped from coronavirus Spike peptide sequences.
References
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Data mining techniques
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Journal ArticleDOI
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Gunjan Verma,Vineeta Verma +1 more
TL;DR: The various application areas where genetic Algorithm plays evolutionary role with data mining technique and explain them in details are discussed.
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