ENHANCED GENE EXPRESSION ANALYSIS USING MODIFIED BIMAX  ALGORITHM FOR CORRELATION-BASED BICLUSTERING

Mr. Manish Kumar Bhardwaj,[2] Dr. Sandeep Singh Rajpoot, Dr. A.P.J. Abdul Kalam

ENHANCED GENE EXPRESSION ANALYSIS USING MODIFIED BIMAX ALGORITHM FOR CORRELATION-BASED BICLUSTERING

Authors

Mr. Manish Kumar Bhardwaj,[2] Dr. Sandeep Singh Rajpoot, Dr. A.P.J. Abdul Kalam

Keywords:

Gene expression, biclustering, correlation-based clustering, ensemble model, bioinformatics, modified Bimax, data mining.

Abstract

Gene expression data analysis is essential for understanding complex biological processes and diseases. Biclustering, apowerful data mining technique, simultaneously groups genes and conditions to reveal patterns. This research aims toidentify all correlated biclusters in gene expression data using a modified Bimax algorithm. By introducing a pre-processing

References

• Ben-Dor, A., Chor, B., Karp, R., & Yakhini, Z. (2003). Discovering local structure in gene expression data: The

order-preserving submatrix problem. Journal of Computational Biology , 10(3-4), 373-384.

• Cheng, Y., & Church, G. M. (2000). Biclustering of expression data. Proceedings of the Eighth International

Conference on Intelligent Systems for Molecular Biology , 8, 93-103.

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Published

2024-08-20

How to Cite

Mr. Manish Kumar Bhardwaj,[2] Dr. Sandeep Singh Rajpoot, Dr. A.P.J. Abdul Kalam. (2024). ENHANCED GENE EXPRESSION ANALYSIS USING MODIFIED BIMAX ALGORITHM FOR CORRELATION-BASED BICLUSTERING. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 5963–5968. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3545