Granular Computing Methods in Bioinformatics* Granular Computing Methods in Bioinformatics
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INTERVAL ANALYSIS-BASED HYPERBOX GRANULAR COMPUTING CLASSIFICATION ALGORITHMS
Representation of a granule, relation and operation between two granules are mainly researched in granular computing. Hyperbox granular computing classification algorithms (HBGrC) are proposed based on interval analysis. Firstly, a granule is represented as the hyperbox which is the Cartesian product of $N$ intervals for classification in the $N$-dimensional space. Secondly, the relation betwee...
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Vital areas in Bioinformatics research is one of the Protein sequence analysis. Protein sequence motifs are determining the structure, function, and activities of the particular protein. The main objective of this paper is to obtain protein sequence motifs which are universally conserved across protein family boundaries. In this research, the input dataset is extremely large. Hence, an efficien...
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Protein sequence motifs are very important to the analysis of biologically significant conserved regions to determine the conformation, function and activities of the proteins. These sequence motifs are identified from protein sequence segments generated from large number of protein sequences. All generated sequence segments may not yield potential motif patterns. In this paper, short recurring...
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Bioinformatics is a field devoted to the interpretation and analysis of biological data using computational techniques. In recent years the study of bioinformatics has grown tremendously due to huge amount of biological information generated by scientific community. Proteins are made up of chain of amino acids. Protein sequence motifs are small fragments of conserved amino acids often associate...
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