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IJMLC 2020 Vol.10(3): 452-457 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2020.10.3.956

Application of K-Means Clustering to Identify Similar Gene Expression Patterns during Erythroid Development

Heba Saadeh, Reem Q. Al Fayez, and Basima Elshqeirat

Abstract—Erythropoiesis is the specific lineage in which the haematopoietic stem cells (HSC) differentiate into red blood cells. During their development, HSC undergo global gene expression changes to reflect the current developmental stage needs. A good way to identify the set of genes that have similar global expression patterns across the different developmental stages is through clustering. Unsupervised clustering aims at highlighting these co-regulated genes without prior knowledge regards their full interactions. In this study, we apply k-means clustering on a gene expression microarray data that measures the expression levels of human genes at four erythropoiesis stages. Eight clusters have been identified; one cluster, in particular, of 450 genes (C4) is more active toward the maturation stages and it is involved in cell division and DNA replication processes, which are vital during development. Another cluster of 234 genes (C7) is involved in autophagy (cells consumption/destruction), which is known to be involved in enucleation (expulsion of the nucleus from the cell).

Index Terms—Clustering, elbow method, erythropoiesis, k-means.

Heba Saadeh and Basima Elshqeirat are with the Department of Computer Science, University of Jordan, Amman, Jordan (e-mail: heba.saadeh@ju.edu.jo, b.shoqurat@ju.edu.jo).
Reem Q. Al Fayez is with the Department of Computer Information Systems, University of Jordan, Amman, Jordan (e-mail: r.alfayez@ju.edu.jo).

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Cite: Heba Saadeh, Reem Q. Al Fayez, and Basima Elshqeirat, "Application of K-Means Clustering to Identify Similar Gene Expression Patterns during Erythroid Development," International Journal of Machine Learning and Computing vol. 10, no. 3, pp. 452-457, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net


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