We have located links that may give you full text access.
Distribution based Fuzzy Estimate Spectral Clustering for Cancer Detection with Protein Sequence and Structural Motifs
Asian Pacific Journal of Cancer Prevention : APJCP 2018 July 28
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.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app