A Top-K formal concepts-based algorithm for mining positive and negative correlation biclusters of DNA microarray data-Reference-Cited by-同舟云学术

A Top-K formal concepts-based algorithm for mining positive and negative correlation biclusters of DNA microarray data

Published:2023-09-12 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Houari Amina^ORCID,Ben Yahia Sadok

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-023-01949-9.pdf

Reference77 articles.

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3. Ayadi W, Hao J (2014) A memetic algorithm for discovering negative correlation biclusters of DNA microarray data. Neurocomputing 145:14–22. https://doi.org/10.1016/j.neucom.2014.05.074

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5. Behera N, Sinha S (2022) Extracting the candidate genes for cancer from the microarray gene expression data by stochastic computation

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