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Review
. 2021 Aug 19:2021:4242646.
doi: 10.1155/2021/4242646. eCollection 2021.

Gene Expression-Assisted Cancer Prediction Techniques

Tanima Thakur  1 , Isha Batra  1 , Monica Luthra  2 , Shanmuganathan Vimal  3 , Gaurav Dhiman  4 , Arun Malik  1 , Mohammad Shabaz  5   6
Affiliations
Review

Gene Expression-Assisted Cancer Prediction Techniques

Tanima Thakur et al. J Healthc Eng. .

Retraction in

Abstract

Cancer is one of the deadliest diseases and with its growing number, its detection and treatment become essential. Researchers have developed various methods based on gene expression. Gene expression is a process that is used to convert deoxyribose nucleic acid (DNA) to ribose nucleic acid (RNA) and then RNA to protein. This protein serves so many purposes, such as creating cells, drugs for cancer, and even hybrid species. As genes carry genetic information from one generation to another, some gene deformity is also transferred to the next generation. Therefore, the deformity needs to be detected. There are many techniques available in the literature to predict cancerous and noncancerous genes from gene expression data. This is an important development from the point of diagnostics and giving a prognosis for the condition. This paper will present a review of some of those techniques from the literature; details about the various datasets on which these techniques are implemented and the advantages and disadvantages.

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Conflict of interest statement

The authors declare that there are no conflicts of interest regarding the publication of this article.

Figures

Figure 1
Figure 1
Comparison of various prediction techniques.
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