Functional analysis of cancer gene subtype from co-clustering and classification
Cancer is a heterogeneity genetic disease with huge phenotypic alterations among dissimilar cancers types or even between same cancer types. Recent expansions of genome-wide profiling technologies offer a chance to explore molecular changes variations throughout advancement of cancer. Therefore, var...
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2020-04-01.
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| LEADER | 02599 am a22003133u 4500 | ||
|---|---|---|---|
| 001 | ijeecs21118_13614 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Machap, Logenthiran |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Abdullah, Afnizanfaizal |e author |
| 700 | 1 | 0 | |a Abdullah, Afnizanfaizal |e author |
| 245 | 0 | 0 | |a Functional analysis of cancer gene subtype from co-clustering and classification |
| 260 | |b Institute of Advanced Engineering and Science, |c 2020-04-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/21118 | ||
| 520 | |a Cancer is a heterogeneity genetic disease with huge phenotypic alterations among dissimilar cancers types or even between same cancer types. Recent expansions of genome-wide profiling technologies offer a chance to explore molecular changes variations throughout advancement of cancer. Therefore, various statistical and machine learning algorithms have been designed and developed for the handling and interpretation of high-throughput microarray molecular data. Discovery of molecular subtypes studies have permitted the cancer to be allocated into similar groups that are deliberated to port similar molecular and clinical characteristics. Thus, the main objective of this research is to discover cancer gene subtypes and classify genes to obtain higher accuracy. In particular improved co-clustering algorithm used to discover cancer subtypes. And then supervised infinite feature selection gene selection method was combined with multi class SVM for classification of selected genes and further biological analysis. The analysis on breast cancer and glioblastoma multiforme evidences that top genes involved in cancer and the pathways present in both cancer top genes. The functional analysis is useful in medical and pharmaceutical field for cancer diagnosis and prognosis. | ||
| 540 | |a Copyright (c) 2019 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
| 546 | |a eng | ||
| 690 | |||
| 690 | |a Microarray, Cancer Subtypes, Co-clustering Classification, Biological analysis | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 18, No 1: April 2020; 343-350 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v18.i1 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/21118/13614 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/21118/13614 |z Get fulltext |