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Detection of Motif in Protein Sequence Using K-Means and Fuzzy C-Means Algorithms

Geethamani. R1 , Kalaivani. B2

Section:Survey Paper, Product Type: Journal Paper
Volume-07 , Issue-08 , Page no. 87-90, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si8.8790

Online published on Apr 10, 2019

Copyright © Geethamani. R, Kalaivani. B . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Geethamani. R, Kalaivani. B, “Detection of Motif in Protein Sequence Using K-Means and Fuzzy C-Means Algorithms,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.08, pp.87-90, 2019.

MLA Style Citation: Geethamani. R, Kalaivani. B "Detection of Motif in Protein Sequence Using K-Means and Fuzzy C-Means Algorithms." International Journal of Computer Sciences and Engineering 07.08 (2019): 87-90.

APA Style Citation: Geethamani. R, Kalaivani. B, (2019). Detection of Motif in Protein Sequence Using K-Means and Fuzzy C-Means Algorithms. International Journal of Computer Sciences and Engineering, 07(08), 87-90.

BibTex Style Citation:
@article{R_2019,
author = { Geethamani. R, Kalaivani. B},
title = {Detection of Motif in Protein Sequence Using K-Means and Fuzzy C-Means Algorithms},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {07},
Issue = {08},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {87-90},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=923},
doi = {https://doi.org/10.26438/ijcse/v7i8.8790}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i8.8790}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=923
TI - Detection of Motif in Protein Sequence Using K-Means and Fuzzy C-Means Algorithms
T2 - International Journal of Computer Sciences and Engineering
AU - Geethamani. R, Kalaivani. B
PY - 2019
DA - 2019/04/10
PB - IJCSE, Indore, INDIA
SP - 87-90
IS - 08
VL - 07
SN - 2347-2693
ER -

           

Abstract

Finding the Motif in biological sequences of protein synthesis is a basic problem in determining the protein structure. Detection of the Motif is used with many applications in gene regulation, protein family identification and determination of functionally and structurally important identities. Large amount of biological data is used to resolve the problem of discovering patterns in biological sequences computationally. In this research, we have designed an approach using a system of clustering in data mining to detect frequently occurring informative motifs that are high in information content. We have proposed a comparative approach for Skin Melanin associated problems(SMA) detection in preliminary stages using protein sequence. We have used the protein sequence with normal and abnormal data as the trained dataset. Test instances are classified into normal to abnormal by comparing it with the fundamental dataset. In this paper, We compare and evaluate the performance of two clustering algorithms namely K-means and fuzzy c-means clustering for protein sequences.

Key-Words / Index Term

clustering ; k-means and fuzzy c-means; SMA

References

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