Implementation of spectral clustering with partitioning around medoids (PAM) algorithm on microarray data of carcinoma

Rosalia D. Cahyaningrum, Alhadi B., Titin Siswantining

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

6 Citations (Scopus)


Technology of microarray became one of the imperative tools in life science to observe the gene expression levels, one of which is the expression of the genes of people with carcinoma. Carcinoma is a cancer that forms in the epithelial tissue. These data can be analyzed such as the identification expressions hereditary gene and also build classifications that can be used to improve diagnosis of carcinoma. Microarray data usually served in large dimension that most methods require large computing time to do the grouping. Therefore, this study uses spectral clustering method which allows to work with any object for reduces dimension. Spectral clustering method is a method based on spectral decomposition of the matrix which is represented in the form of a graph. After the data dimensions are reduced, then the data are partitioned. One of the famous partition method is Partitioning Around Medoids (PAM) which is minimize the objective function with exchanges all the non-medoid points into medoid point iteratively until converge. Objectivity of this research is to implement methods spectral clustering and partitioning algorithm PAM to obtain groups of 7457 genes with carcinoma based on the similarity value. The result in this study is two groups of genes with carcinoma.

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


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