Gene classification and pattern extraction from gene sequence data is essential in understanding different gene sequence features. The field of gene expression data analysis has grown in the past few years from being purely data-centric to integrative, aiming at complementing micro-array analysis with data and knowledge from diverse available sources. Since then, it has been used for various science fields, including the discovery of new drugs, identification of protein coded genes by analyzing and separating exons from the main sequence, phenotype prediction based on gene expression. This paper presents an application of gene classification from gene sequence data using data mining and machine learning techniques. Our research’s main goal is to compare different machine learning approaches based on time of execution, and overall efficiency by testing them on different micro-array datasets of gene sequence and determining the best approach for gene classification. Eight different machine learning techniques have been tested on eleven different gene expression datasets. We also apply feature selection method before we apply classification techniques on the gene expression datasets. The experimental results show that feature selection method improve the performance of the techniques on the gene expression datasets. Moreover, we perform pattern analysis on some gene expression datasets using J48 decision tree outcome.
|Title of host publication||2021 IEEE International Conference on Machine Learning and Cybernetics (ICMLC)|
|Place of Publication||United States|
|Number of pages||9|
|ISBN (Print)||9781665466097 (Print on demand)|
|Publication status||Published - 24 Mar 2022|
|Event||20th International Conference on Machine Learning and Cybernetics (ICMLC) 2021 - University of Adelaide (virtual conference), Adelaide, Australia|
Duration: 04 Dec 2021 → 05 Dec 2021
https://web.archive.org/web/20211026172833/https://icmlc.com/ (Conference website)
|Name||International Conference on Machine Learning and Cybernetics|
|Conference||20th International Conference on Machine Learning and Cybernetics (ICMLC) 2021|
|Period||04/12/21 → 05/12/21|
|Other||The International Conference on Machine Learning and Cybernetics (ICMLC) is entering its 20th year while the International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR) is marching towards its 18th anniversary, we are all excited and committed to our vision: organizing good quality international conferences that provide valuable educational services to young researchers in the Asia region, particularly researchers in China.|
This year features keynotes and tutorial on Adversarial Learning, and a special issue with Springer’s Journal of Machine Learning and Cybernetics.
In addition to keynote speakers, the two conferences offer free tutorials, Lotfi Zadeh Best Paper Awards, special issues of SCI indexed journals, and plenty of opportunities for you to build up your own professional network while you can come and meet with the Editors-In-Chief, IEEE Fellows and the IEEE Systems, Man and Cybernetics Society leaders.