Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman

Clustering is an overlapping method found in many areas such as data mining, machine learning, pattern recognition, bioinformatics and information retrieval. The goal of clustering is to group any similar objects into a cluster, while the other objects that are not similar in the different clusters....

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Main Author: Seman, Ali
Format: Book Section
Language:English
Published: Institute of Graduate Studies, UiTM 2013
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Online Access:http://ir.uitm.edu.my/id/eprint/19128/1/ABS_ALI%20SEMAN%20TDRA%20VOL%204%20IGS%2013.pdf
http://ir.uitm.edu.my/id/eprint/19128/
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Institution: Universiti Teknologi Mara
Language: English
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spelling my.uitm.ir.191282018-06-11T04:28:15Z http://ir.uitm.edu.my/id/eprint/19128/ Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman Seman, Ali Malaysia Clustering is an overlapping method found in many areas such as data mining, machine learning, pattern recognition, bioinformatics and information retrieval. The goal of clustering is to group any similar objects into a cluster, while the other objects that are not similar in the different clusters. Meanwhile, Y-Short Tandem Repeats (Y-STR) is the tandem repeats on Y-Chromosome. The Y-STR data is now being utilized for distinguishing lineages and their relationships applied in many applications such as genetic genealogy, forensic genetic and anthropological genetic applications. This research tends to partition the Y-STR data into groups of similar genetic distances. The genetic distance is measured by comparing the allele values and their modal haplotypes. Nevertheless, the distances among the Y-STR data are typically found similar or very similar to each other. They are characterized by the higher degree of similarity of objects in intra-classes and also inter-classes. In some cases, they are quite distant and sparseness… Institute of Graduate Studies, UiTM 2013 Book Section PeerReviewed text en http://ir.uitm.edu.my/id/eprint/19128/1/ABS_ALI%20SEMAN%20TDRA%20VOL%204%20IGS%2013.pdf Seman, Ali (2013) Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman. In: The Doctoral Research Abstracts. IPSis Biannual Publication, 4 (4). Institute of Graduate Studies, UiTM, Shah Alam.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Malaysia
spellingShingle Malaysia
Seman, Ali
Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman
description Clustering is an overlapping method found in many areas such as data mining, machine learning, pattern recognition, bioinformatics and information retrieval. The goal of clustering is to group any similar objects into a cluster, while the other objects that are not similar in the different clusters. Meanwhile, Y-Short Tandem Repeats (Y-STR) is the tandem repeats on Y-Chromosome. The Y-STR data is now being utilized for distinguishing lineages and their relationships applied in many applications such as genetic genealogy, forensic genetic and anthropological genetic applications. This research tends to partition the Y-STR data into groups of similar genetic distances. The genetic distance is measured by comparing the allele values and their modal haplotypes. Nevertheless, the distances among the Y-STR data are typically found similar or very similar to each other. They are characterized by the higher degree of similarity of objects in intra-classes and also inter-classes. In some cases, they are quite distant and sparseness…
format Book Section
author Seman, Ali
author_facet Seman, Ali
author_sort Seman, Ali
title Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman
title_short Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman
title_full Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman
title_fullStr Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman
title_full_unstemmed Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman
title_sort partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / ali seman
publisher Institute of Graduate Studies, UiTM
publishDate 2013
url http://ir.uitm.edu.my/id/eprint/19128/1/ABS_ALI%20SEMAN%20TDRA%20VOL%204%20IGS%2013.pdf
http://ir.uitm.edu.my/id/eprint/19128/
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