Experimental analysis of iterative-scaling fuzzy additive spectral clustering (is-FADDIS) for cancer subtypess identification

Muhamad Fathurahman, Ionia Veritawati, Ito Wasito

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Identification of cancer subtypes based on gene expression data plays an important role to develope an appropriate therapy for the patient. However, the analysis of gene expression data related to cancer subtypes identification have many difficulties such as, high dimensional attributes, missing values and sparse data problem. To solve this problem, Iterative Scalling Fuzzy Additive Spectral Clustering (is-FADDIS) will be introduced. This research aims to compare the performance of is-FADDIS to other popular clustering techniques including Gaussian Mixture Clustering and Auto K-Means on the basis of Subtypess Cancer Identification in Human Colorectal Carcinoma and B-Cell Lymphoma dataset. The result of the experiment shows that is-FADDIS successfully produce three cluster structures in Human Colorectal Carcinoma and two well separated cluster structures in B-Cell Lymphoma dataset.

Original languageEnglish
Title of host publication2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages435-440
Number of pages6
ISBN (Electronic)9781728101354
DOIs
Publication statusPublished - 17 Jan 2019
Event10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018 - Yogyakarta, Indonesia
Duration: 27 Oct 201828 Oct 2018

Publication series

Name2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018

Conference

Conference10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
CountryIndonesia
CityYogyakarta
Period27/10/1828/10/18

Keywords

  • Gene Clustering
  • Is-FADDIS
  • Subtypes Cancer Identification

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    Fathurahman, M., Veritawati, I., & Wasito, I. (2019). Experimental analysis of iterative-scaling fuzzy additive spectral clustering (is-FADDIS) for cancer subtypess identification. In 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018 (pp. 435-440). [8618225] (2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACSIS.2018.8618225