Gene expression data classification and pattern analysis using data driven approach

Aiman Jabeen Ramisa, Ananna Hossain, Sk Md Injamul Islam, Ponuel Mollah Swadesh, Md. Toushif Islam, Md Anisur Rahman, Mohammad Zavid Parvez

Research output: Book chapter/Published conference paperConference paperpeer-review

Abstract

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.
Original languageEnglish
Title of host publication2021 IEEE International Conference on Machine Learning and Cybernetics (ICMLC)
Place of PublicationUnited States
PublisherIEEE
Number of pages9
ISBN (Electronic)9781665466080
ISBN (Print)9781665466097 (Print on demand)
DOIs
Publication statusPublished - 24 Mar 2022
Event20th International Conference on Machine Learning and Cybernetics (ICMLC) 2021 - University of Adelaide (virtual conference), Adelaide, Australia
Duration: 04 Dec 202105 Dec 2021
https://web.archive.org/web/20211026172833/https://icmlc.com/ (Conference website)

Publication series

NameInternational Conference on Machine Learning and Cybernetics
PublisherIEEE
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Conference

Conference20th International Conference on Machine Learning and Cybernetics (ICMLC) 2021
Country/TerritoryAustralia
CityAdelaide
Period04/12/2105/12/21
OtherThe 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.
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