TY - GEN
T1 - Experimental analysis of iterative-scaling fuzzy additive spectral clustering (is-FADDIS) for cancer subtypess identification
AU - Fathurahman, Muhamad
AU - Veritawati, Ionia
AU - Wasito, Ito
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - 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.
AB - 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.
KW - Gene Clustering
KW - Is-FADDIS
KW - Subtypes Cancer Identification
UR - http://www.scopus.com/inward/record.url?scp=85062383383&partnerID=8YFLogxK
U2 - 10.1109/ICACSIS.2018.8618225
DO - 10.1109/ICACSIS.2018.8618225
M3 - Conference contribution
AN - SCOPUS:85062383383
T3 - 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
SP - 435
EP - 440
BT - 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
Y2 - 27 October 2018 through 28 October 2018
ER -
