Title :
Protein Superfamily Classification Using Fuzzy Rule-Based Classifier
Author :
Mansoori, Eghbal G. ; Zolghadri, Mansoor J. ; Katebi, Seraj D.
Author_Institution :
Dept. of Comput. Sci. & Eng., Shiraz Univ., Shiraz
fDate :
3/1/2009 12:00:00 AM
Abstract :
In this paper, we have proposed a fuzzy rule-based classifier for assigning amino acid sequences into different superfamilies of proteins. While the most popular methods for protein classification rely on sequence alignment, our approach is alignment-free and so more human readable. It accounts for the distribution of contiguous patterns of n amino acids ( n-grams) in the sequences as features, alike other alignment-independent methods. Our approach, first extracts a plenty of features from a set of training sequences, then selects only some best of them, using a proposed feature ranking method. Thereafter, using these features, a novel steady-state genetic algorithm for extracting fuzzy classification rules from data is used to generate a compact set of interpretable fuzzy rules. The generated rules are simple and human understandable. So, the biologists can utilize them, for classification purposes, or incorporate their expertise to interpret or even modify them. To evaluate the performance of our fuzzy rule-based classifier, we have compared it with the conventional nonfuzzy C4.5 algorithm, beside some other fuzzy classifiers. This comparative study is conducted through classifying the protein sequences of five superfamily classes, downloaded from a public domain database. The obtained results show that the generated fuzzy rules are more interpretable, with acceptable improvement in the classification accuracy.
Keywords :
bioinformatics; feature extraction; fuzzy set theory; genetic algorithms; molecular biophysics; pattern classification; proteins; alignment-independent method; amino acid sequence; feature extraction; fuzzy rule-based classifier; nonfuzzy C4.5 algorithm; protein classification; protein superfamily classification; public domain database; steady-state genetic algorithm; Feature extraction; fuzzy rule-based classifier; genetic algorithm; protein superfamily classification; Algorithms; Amino Acid Sequence; Fuzzy Logic; Molecular Sequence Data; Pattern Recognition, Automated; Proteins; Sequence Alignment; Sequence Analysis, Protein; Sequence Homology, Amino Acid;
Journal_Title :
NanoBioscience, IEEE Transactions on
DOI :
10.1109/TNB.2009.2016484