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OJBTM
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)
ABSTRACT
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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