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Online Journal of Bioinformatics ©
Volume 15 (3): 243-252, 2014.
Data mining techniques for biological sequence classification
Anubha Dubey PhD.
Department of Bioinformatics,MANIT, BHOPAL (M.P)
Dubey A., Data mining techniques for biological sequence classification, Onl J Bioinform., 15 (3): 243-252, 2014. The voluminous amount of gene data, microarrays, nucleotides and peptide sequences of bacteria, fungi, virus and other organisms generate useful information about disease processes. Because wet lab sequence analysis is time consuming and expensive, there is a need to develop data mining techniques and machine learning models to extract information from data. Usually classification is a preliminary step for examining a set of cases that can be grouped based on similarity to each other. Data mining techniques/tools for bio molecular sequences and data classification such as WEKA, SVM, Fuzzy-sets and others are described
Keywords: WEKA, SVM, Fuzzy-set, Classification, Sequence, Microarray.
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