Implementation of spectral clustering on microarray data of carcinoma using k -means algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)


Clustering is one of data analysis methods that aims to classify data which have similar characteristics in the same group. Spectral clustering is one of the most popular modern clustering algorithms. As an effective clustering technique, spectral clustering method emerged from the concepts of spectral graph theory. Spectral clustering method needs partitioning algorithm. There are some partitioning methods including PAM, SOM, Fuzzy c-means, and k-means. Based on the research that has been done by Capital and Choudhury in 2013, when using Euclidian distance k-means algorithm provide better accuracy than PAM algorithm. So in this paper we use k-means as our partition algorithm. The major advantage of spectral clustering is in reducing data dimension, especially in this case to reduce the dimension of large microarray dataset. Microarray data is a small-sized chip made of a glass plate containing thousands and even tens of thousands kinds of genes in the DNA fragments derived from doubling cDNA. Application of microarray data is widely used to detect cancer, for the example is carcinoma, in which cancer cells express the abnormalities in his genes. The purpose of this research is to classify the data that have high similarity in the same group and the data that have low similarity in the others. In this research, Carcinoma microarray data using 7457 genes. The result of partitioning using k-means algorithm is two clusters.

Original languageEnglish
Title of host publicationSymposium on Biomathematics, SYMOMATH 2016
EditorsBeben Benyamin, Kasbawati
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735414938
Publication statusPublished - 27 Mar 2017
Event4th International Symposium on Biomathematics, SYMOMATH 2016 - Makassar, Indonesia
Duration: 7 Oct 20169 Oct 2016

Publication series

NameAIP Conference Proceedings
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616


Conference4th International Symposium on Biomathematics, SYMOMATH 2016


Dive into the research topics of 'Implementation of spectral clustering on microarray data of carcinoma using k -means algorithm'. Together they form a unique fingerprint.

Cite this