The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Role of Data Mining Techniques in Bioinformatics
Abstract
Data mining offers a highly effective technique that is useful in research and development of bioinformatics. Bioinformatics consists biological information such as DNA, RNA, and protein. Data mining tasks/techniques are classification, prediction, clustering, association, outlier detection, regression, and pattern tracking. Data mining provides important correlation, hidden patterns, and knowledge from the bioinformatics data set. This paper presents the role of data mining techniques in bioinformatics application. Classification of gene and protein structure, analyzing the gene expression, association of co-disease, outlier detection and gene selection, protein structure prediction, and drug discovery are some typical biological example that has proven data mining as a suitable technique for bioinformatics.
Related Content
Linkon Chowdhury, Md Sarwar Kamal, Shamim H. Ripon, Sazia Parvin, Omar Khadeer Hussain, Amira Ashour, Bristy Roy Chowdhury.
© 2024.
20 pages.
|
Mousomi Roy.
© 2024.
21 pages.
|
Nassima Dif, Zakaria Elberrichi.
© 2024.
20 pages.
|
Pyingkodi Maran, Shanthi S., Thenmozhi K., Hemalatha D., Nanthini K..
© 2024.
16 pages.
|
Mohamed Nadjib Boufenara, Mahmoud Boufaida, Mohamed Lamine Berkane.
© 2024.
16 pages.
|
Meroua Daoudi, Souham Meshoul, Samia Boucherkha.
© 2024.
25 pages.
|
Zhongyu Lu, Qiang Xu, Murad Al-Rajab, Lamogha Chiazor.
© 2024.
56 pages.
|
|
|