Distribution based Fuzzy Estimate Spectral Clustering for Cancer Detection with Protein Sequence and Structural Motifs
Asian Pac J Cancer Prev
; 19(7): 1935-1940, 2018 Jul 27.
Article
em En
| MEDLINE
| ID: mdl-30051675
ABSTRACT
Objective:
In biological data analysis, protein sequence and structural motifs are an amino-acid sequence patterns that are widespread and used as tools for detecting the cancer at an earlier stage. To improve the cancer detection with minimum space and time complexity, Distribution based Fuzzy Estimate Spectral Clustering (DFESC) technique is developed.Methods:
Initially, the protein sequence motifs are taken from dataset to form the cluster. The Distribution based spectral clustering is applied to group the protein sequence by measuring the generalized jaccard similarity between each protein sequences. To develop the clustering accuracy, soft computing technique namely fuzzy logic is applied to calculate membership value of each sequence motifs.Results:
The outcome showed that the presented DFESC technique effectively identifies the cancer in terms of clustering accuracy, false positive rate, and cancer detection time and space complexity.Conclusion:
Based on the observations, evaluation of DFESC technique provides improved result for premature detection of cancer using protein sequence and structural motifs.Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Biomarcadores Tumorais
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Lógica Fuzzy
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Motivos de Aminoácidos
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Neoplasias
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article