APPLY DATA CLUSTERING TO GENE EXPRESSION DATA

APPLY DATA CLUSTERING TO GENE EXPRESSION DATA

Data clustering plays an important role in effective analysis of gene expression. Although DNA microarray technology facilitates expression monitoring, several challenges arise when dealing with gene expression datasets. Some of these challenges are the enormous number of genes, the dimensionality o...

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Bibliographic Details
Main Author: Abualhamayl, Abdullah Jameel, Mr.
Format: Others
Published: CSUSB ScholarWorks 2015
Subjects:
Clustering
Gene
Dataset
Expression
Time Series
R Language
Analysis
Bioinformatics
Genetics
Online Access:https://scholarworks.lib.csusb.edu/etd/259
https://scholarworks.lib.csusb.edu/cgi/viewcontent.cgi?article=1293&context=etd
id ndltd-csusb.edu-oai-scholarworks.lib.csusb.edu-etd-1293
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spelling ndltd-csusb.edu-oai-scholarworks.lib.csusb.edu-etd-12932019-10-23T03:35:58Z APPLY DATA CLUSTERING TO GENE EXPRESSION DATA Abualhamayl, Abdullah Jameel, Mr. Data clustering plays an important role in effective analysis of gene expression. Although DNA microarray technology facilitates expression monitoring, several challenges arise when dealing with gene expression datasets. Some of these challenges are the enormous number of genes, the dimensionality of the data, and the change of data over time. The genetic groups which are biologically interlinked can be identified through clustering. This project aims to clarify the steps to apply clustering analysis of genes involved in a published dataset. The methodology for this project includes the selection of the dataset representation, the selection of gene datasets, Similarity Matrix Selection, the selection of clustering algorithm, and analysis tool. R language with the focus of Kmeans, fpc, hclust, and heatmap3 packages in R is used in this project as an analysis tool. Different clustering algorithms are used on Spellman dataset to illustrate how genes are grouped together in clusters which help to understand our genetic behaviors. 2015-12-01T08:00:00Z text application/pdf https://scholarworks.lib.csusb.edu/etd/259 https://scholarworks.lib.csusb.edu/cgi/viewcontent.cgi?article=1293&context=etd Electronic Theses, Projects, and Dissertations CSUSB ScholarWorks Clustering Gene Dataset Expression Time Series R Language Analysis Bioinformatics Genetics
collection NDLTD
format Others
sources NDLTD
topic Clustering
Gene
Dataset
Expression
Time Series
R Language
Analysis
Bioinformatics
Genetics
spellingShingle Clustering
Gene
Dataset
Expression
Time Series
R Language
Analysis
Bioinformatics
Genetics
Abualhamayl, Abdullah Jameel, Mr.
APPLY DATA CLUSTERING TO GENE EXPRESSION DATA
description Data clustering plays an important role in effective analysis of gene expression. Although DNA microarray technology facilitates expression monitoring, several challenges arise when dealing with gene expression datasets. Some of these challenges are the enormous number of genes, the dimensionality of the data, and the change of data over time. The genetic groups which are biologically interlinked can be identified through clustering. This project aims to clarify the steps to apply clustering analysis of genes involved in a published dataset. The methodology for this project includes the selection of the dataset representation, the selection of gene datasets, Similarity Matrix Selection, the selection of clustering algorithm, and analysis tool. R language with the focus of Kmeans, fpc, hclust, and heatmap3 packages in R is used in this project as an analysis tool. Different clustering algorithms are used on Spellman dataset to illustrate how genes are grouped together in clusters which help to understand our genetic behaviors.
author Abualhamayl, Abdullah Jameel, Mr.
author_facet Abualhamayl, Abdullah Jameel, Mr.
author_sort Abualhamayl, Abdullah Jameel, Mr.
title APPLY DATA CLUSTERING TO GENE EXPRESSION DATA
title_short APPLY DATA CLUSTERING TO GENE EXPRESSION DATA
title_full APPLY DATA CLUSTERING TO GENE EXPRESSION DATA
title_fullStr APPLY DATA CLUSTERING TO GENE EXPRESSION DATA
title_full_unstemmed APPLY DATA CLUSTERING TO GENE EXPRESSION DATA
title_sort apply data clustering to gene expression data
publisher CSUSB ScholarWorks
publishDate 2015
url https://scholarworks.lib.csusb.edu/etd/259
https://scholarworks.lib.csusb.edu/cgi/viewcontent.cgi?article=1293&context=etd
work_keys_str_mv AT abualhamaylabdullahjameelmr applydataclusteringtogeneexpressiondata
_version_ 1719275645558587392

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