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Knowledge Discovery in Protein Sequence Analysis Using Hierarchical Clustering Method

Desai Farhana
2021 International Journal of Current Research and Review  
The clustering technique is an unsupervised method in data mining. Hierarchical Clustering techniques are useful to represent relationships between protein families.  ...  Conclusion: The hierarchical clustering will help the biologist to judge which genes were clustered rightfully by viewing the tree structure. e the dendrogram.  ...  The above figure shows the results of a hierarchical cluster analysis of the sequence.  ... 
doi:10.31782/ijcrr.2021.131907 fatcat:byvgcel3anaivj2iq5vuz36fba

E-commerce Analysis in selected European Union Countries: Position of Croatia

Nataša Kurnoga, Ana Slišković
2017 Croatian Review of Economic, Business and Social Statistics  
Furthermore, hierarchical and non-hierarchical cluster analyses were used to classify the countries, first at the EU level and then at the level of the post-transition EU countries.  ...  Finally, the cluster analysis resulted in the following three clusters: most developed, developed and less developed.  ...  Author can be contacted at Ana  ... 
doi:10.1515/crebss-2017-0009 fatcat:k2rlysbuxrh4rdburu6p2glwhm


Aastha Gupta, Himanshu Sharma, Anas Akhtar
2021 EPRA international journal of multidisciplinary research  
Two clustering methods, k-means and hierarchical clustering, are explained in this survey and their analysis using WEKA tool on different data sets.  ...  KEYWORDS: data clustering, weka , k-means, hierarchical clustering  ...  Setnes, "Extended fuzzy clustering algorithms" [6] The author uses fuzzy clustering algorithm to divide dataset into clusters.  ... 
doi:10.36713/epra8308 fatcat:m5tnyqi2uvclfmlxqimwwtriva

To Study the Seismic Behaviour of Multi Storeyed Building along with Planning at Various Zones using Hierarchical Agglomerative Clustering

Chandra Kumar Nimmana
2018 International Journal for Research in Applied Science and Engineering Technology  
From the Cluster Dendrogram, we can note the hierarchical gradation based on the distance between the cities which can be used for efficient governance.  ...  This first part of this research is to find the structural coordinate determination for optimal administrative offices stationing using Agglomerative Hierarchical Clustering.  ...  The authors also are grateful to the former HOD Prof Ch. Kannam Naidu (AITAM). The authors also express their gratitude to Prof Murali Monangi (formerly at AITAM).  ... 
doi:10.22214/ijraset.2018.3078 fatcat:xvzuavbk7jdzxpxevv4gtjdqv4

HiVis: a portable, scalable tool for hierarchical visualization and analysis of biological networks

Zhiwen Qiang, Hao Chen, Xiaopeng Zhu, Shikui Tu
2018 Applied Informatics  
Methods We use a top-down approach to cluster the biological networks into a multi-level nodelink graph.  ...  HiVis provides a hierarchical view of the networks through a zoom-in or zoom-out function powered by k-means and fast approximate spectral clustering algorithms.  ...  Competing interests The authors declare that they have no competing interests.  ... 
doi:10.1186/s40535-018-0050-0 fatcat:osaczlfbyre4vhdsvqqhrg7x2i

A Fast Quad-Tree Based Two Dimensional Hierarchical Clustering

Priscilla Rajadurai, Swamynathan Sankaranarayanan
2012 Bioinformatics and Biology Insights  
The proposed technique focuses on a QT based fast 2-dimensional hierarchical clustering algorithm to perform clustering.  ...  Cluster analysis partitions a given dataset into groups based on specified features.  ...  Acknowledgements The Authors express their sincere thanks to the Department of Information Science and Technology, Anna University, Chennai for providing necessary facilities to conduct their research.  ... 
doi:10.4137/bbi.s10383 pmid:23226009 pmcid:PMC3511054 fatcat:cgb4lbu7mjfpfh3yleckbwxcx4

Authorship Verification of Online Messages for Forensic Investigation

Smita Nirkhi, R.V. Dharaskar, V.M. Thakare
2016 Procedia Computer Science  
Fig-1 shows result for cluster analysis using hierarchical clustering. Three separate clusters for 3 authors are shown in here. Fig-2 shows Multidimensional scaling for three authors.  ...  The last stage of the analysis involves a human interpretation of the generated plots. Hierarchical Clustering The hierarchical clustering algorithm builds a hierarchy of clusters.  ... 
doi:10.1016/j.procs.2016.02.111 fatcat:erggatgo7fhm3hfdudwxv2pvfu

Higra: Hierarchical Graph Analysis

B. Perret, G. Chierchia, J. Cousty, S.J. F. Guimarães, Y. Kenmochi, L. Najman
2019 SoftwareX  
The main aspects of hierarchical graph analysis addressed in Higra are the construction of hierarchical representations (agglomerative clustering, mathematical morphology hierarchies, etc.), the analysis  ...  Higra -Hierarchical Graph Analysis is a C++/Python library for efficient sparse graph analysis with a special focus on hierarchical methods capable of handling large amount of data.  ...  Acknowledgements The authors are grateful to CNPq (Universal 421521/  ... 
doi:10.1016/j.softx.2019.100335 fatcat:hmgnylzgenh25n5iry5q3kg7hm

Technique of Gene Expression Profiles Extraction Based on the Complex Use of Clustering and Classification Methods

Sergii Babichev, Jiří Škvor
2020 Diagnostics  
clustering of gene expression profiles at hierarchical levels from 1 to 10 using the SOTA (Self-Organizing Tree Algorithm) clustering algorithm with correlation distance metric.  ...  The effectiveness of the appropriate technique was evaluated based on the use of ROC (Receiver Operating Characteristic) analysis using criteria, included as the components, the errors of both the first  ...  The analysis of the obtained results has also shown the reasonability of using the cluster obtained at hierarchical level 7 for further research.  ... 
doi:10.3390/diagnostics10080584 pmid:32806785 fatcat:bazrp6mfgjdilk7a6jjhkxtmme

A parameter-free hybrid clustering algorithm used for malware categorization

ZhiXue Han, Shaorong Feng, Yanfang Ye, Qingshan Jiang
2009 2009 3rd International Conference on Anti-counterfeiting, Security, and Identification in Communication  
quality clusters and it can be well used for malware categorization.  ...  In this paper, resting on the analysis of the extracted instruction of malware samples, we propose a novel parameter-free hybrid clustering algorithm (PFHC) which combines the merits of hierarchical clustering  ...  ACKNOWLEDGMENT The authors would like to thank the members in the Antivirus Lab at Kingsoft Corporation for their helpful discussions and suggestions.  ... 
doi:10.1109/icasid.2009.5276982 fatcat:6dh7xbhvt5hbtfe5mm4sdnfmha

Identification of Asthma Subtypes Using Clustering Methodologies

Matea Deliu, Matthew Sperrin, Danielle Belgrave, Adnan Custovic
2016 Pulmonary Therapy  
The use of unsupervised clustering in adult and paediatric populations has identified subtypes of asthma based on observable characteristics such as symptoms, lung function, atopy, eosinophilia, obesity  ...  Here we describe different clustering methods and demonstrate their contributions to our understanding of the spectrum of asthma syndrome.  ...  then used in hierarchical clustering.  ... 
doi:10.1007/s41030-016-0017-z pmid:27512723 pmcid:PMC4959136 fatcat:mbuimjxqincbfetomyhdbfcccm

Hierarchical and Non-Hierarchical Linear and Non-Linear Clustering Methods to "Shakespeare Authorship Question"

Refat Aljumily
2015 Social Sciences  
More specifically, the mathematically based methodology used here is based on Mean Proximity, as a linear hierarchical clustering method, and on Principal Components Analysis, as a non-hierarchical linear  ...  clustering method.  ...  Conflicts of Interest The author declares no conflict of interest.  ... 
doi:10.3390/socsci4030758 fatcat:rx2pikivyfeethy6gxt3c5hyu4

Cluster analysis of the economic activity of Slovak companies regarding potential indicators of earnings management

Marek Durica, Lucia Svabova, T. Kliestik
2021 SHS Web of Conferences  
Based on hierarchical cluster analysis we identify groups of economic activities (according to the international NACE classification) with similar financial characteristics.  ...  After a precise pre-preparation of the dataset, we use the standard clustering procedures.  ...  The methods used to cluster objects are most often divided into the hierarchical and non-hierarchical, according to how the system forms the resulting clusters.  ... 
doi:10.1051/shsconf/20219207018 fatcat:dhd53uqzffc6he44ecegxbeuc4

Application of Expectation Maximization Method for Purchase Decision-Making Support in Welding Branch

Agnieszka Kujawińska, Michał Rogalewicz, Magdalena Diering
2016 Management and Production Engineering Review  
The proposed approach to cluster analysis is proved as useful in supporting purchase decisions.  ...  The authors analyze the usefulness of the non-hierarchical method, Expectation Maximization (EM), in the selection of material (212 combinations of flux and wire melt) for the SAW (Submerged Arc Welding  ...  The authors decided to use four clusters (k = 4) and to apply this number as a parameter for further analysis with the se- lected non-hierarchical method -Expectation Maximization.  ... 
doi:10.1515/mper-2016-0014 fatcat:d5rthzavhnhgvbaiecz5mg2tve

Current State-of-the-Art of Clustering Methods for Gene Expression Data with RNA-Seq [chapter]

Ismail Jamail, Ahmed Moussa
2020 Pattern Recognition [Working Title]  
There are many clustering and classification algorithms that can be applied in gene expression experiments, the most widely used are hierarchical clustering, k-means clustering and model-based clustering  ...  In addition, we discuss challenges in cluster analysis, and compare the performance of height commonly used clustering methods on four different public datasets from recount2.  ...  Clustering methods based on normal distribution Hierarchical methods Hierarchical clustering method is the most popular method for gene expression data analysis.  ... 
doi:10.5772/intechopen.94069 fatcat:rko4wcgzzbfxvnkaxulf2gljma
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