Cancer classification from DNA microarray data using mRMR and artificial neural network
Cancer is the uncontrolled growth of abnormal cells in the body and is a major death cause now a days. Cancer may arise anywhere in the human body, and it names are remarked as body parts such as colon cancer, lung cancer, breast cancer. It is notable that cancer treatment is much easier in the init...
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2016
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| Online Access: | http://irep.iium.edu.my/51762/ http://irep.iium.edu.my/51762/1/51762_Cancer_Classification_from_DNA.pdf |
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iium-517622016-08-23T07:26:21Z http://irep.iium.edu.my/51762/ Cancer classification from DNA microarray data using mRMR and artificial neural network Akhand, M. A. H Miah, Md. Asaduzzaman Mir , Hussain Kabir Rahman, M.M. Hafizur TK Electrical engineering. Electronics Nuclear engineering Cancer is the uncontrolled growth of abnormal cells in the body and is a major death cause now a days. Cancer may arise anywhere in the human body, and it names are remarked as body parts such as colon cancer, lung cancer, breast cancer. It is notable that cancer treatment is much easier in the initial stage rather than it outbreaks. DNA microarray based gene expression profiling has become efficient technique for cancer identification in early stage and a number of studies are available in this regard. Existing methods used different feature selection methods (e.g., wrapper and filter approaches) to select relevant genes and then employed distinct classifiers (e.g., artificial neural network, Naive Bayes, Decision Tree, Support Vector Machine) to identify cancer. This study considered information theoretic based minimum Redundancy Maximum Relevance (mRMR)method to select important genes and then employed artificial neural network (ANN) for cancer classification. Proposed mRMR-ANN method has been tested on a suite of benchmark data sets of various cancer. Experimental results revealed the proposed method as an effective method for cancer classification when performance compared with several related exiting methods. 2016-08-22 Conference or Workshop Item NonPeerReviewed application/pdf en http://irep.iium.edu.my/51762/1/51762_Cancer_Classification_from_DNA.pdf Akhand, M. A. H and Miah, Md. Asaduzzaman and Mir , Hussain Kabir and Rahman, M.M. Hafizur (2016) Cancer classification from DNA microarray data using mRMR and artificial neural network. In: 2nd International Conference on Engineering, Technologies, and Social Sciences (ICETSS 2016), 22nd-24th Aug. 2016, Kuala Lumpur. (Unpublished) |
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Digital Repository |
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Local University |
| institution |
International Islamic University Malaysia |
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IIUM Repository |
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Online Access |
| language |
English |
| topic |
TK Electrical engineering. Electronics Nuclear engineering |
| spellingShingle |
TK Electrical engineering. Electronics Nuclear engineering Akhand, M. A. H Miah, Md. Asaduzzaman Mir , Hussain Kabir Rahman, M.M. Hafizur Cancer classification from DNA microarray data using mRMR and artificial neural network |
| description |
Cancer is the uncontrolled growth of abnormal cells in the body and is a major death cause now a days. Cancer may arise anywhere in the human body, and it names are remarked as body parts such as colon cancer, lung cancer, breast cancer. It is notable that cancer treatment is much easier in the initial stage rather than it outbreaks. DNA microarray based gene expression profiling has become efficient technique for cancer identification in early stage and a number of studies are available in this regard. Existing methods used different feature selection methods (e.g., wrapper and filter approaches) to select relevant genes and then employed distinct classifiers (e.g., artificial neural network, Naive Bayes, Decision Tree, Support Vector Machine) to identify cancer. This study considered information theoretic based minimum Redundancy Maximum Relevance (mRMR)method to select important genes and then employed artificial neural network (ANN) for cancer classification. Proposed mRMR-ANN method has been tested on a suite of benchmark data sets of various cancer. Experimental results revealed the proposed method as an effective method for cancer classification when performance compared with several related exiting methods. |
| format |
Conference or Workshop Item |
| author |
Akhand, M. A. H Miah, Md. Asaduzzaman Mir , Hussain Kabir Rahman, M.M. Hafizur |
| author_facet |
Akhand, M. A. H Miah, Md. Asaduzzaman Mir , Hussain Kabir Rahman, M.M. Hafizur |
| author_sort |
Akhand, M. A. H |
| title |
Cancer classification from DNA microarray data using mRMR and artificial neural network |
| title_short |
Cancer classification from DNA microarray data using mRMR and artificial neural network |
| title_full |
Cancer classification from DNA microarray data using mRMR and artificial neural network |
| title_fullStr |
Cancer classification from DNA microarray data using mRMR and artificial neural network |
| title_full_unstemmed |
Cancer classification from DNA microarray data using mRMR and artificial neural network |
| title_sort |
cancer classification from dna microarray data using mrmr and artificial neural network |
| publishDate |
2016 |
| url |
http://irep.iium.edu.my/51762/ http://irep.iium.edu.my/51762/1/51762_Cancer_Classification_from_DNA.pdf |
| first_indexed |
2023-09-18T21:13:22Z |
| last_indexed |
2023-09-18T21:13:22Z |
| _version_ |
1777411400903163904 |