Gene Expression-Assisted Cancer Prediction Techniques

Author:

Thakur Tanima1ORCID,Batra Isha1ORCID,Luthra Monica2ORCID,Vimal Shanmuganathan3ORCID,Dhiman Gaurav4ORCID,Malik Arun1ORCID,Shabaz Mohammad56ORCID

Affiliation:

1. School of Computer Science and Engineering, Lovely Professional University, Jalandhar, India

2. Chandigarh University, Chandigarh, Punjab, India

3. Department of CSE, Ramco Institute of Technology, Rajapalayam, Tamil Nadu, India

4. Department of Computer Science, Government Bikram College of Commerce, Patiala, India

5. Arba Minch University, Arba Minch, Ethiopia

6. Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India

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.

Publisher

Hindawi Limited

Subject

Health Informatics,Biomedical Engineering,Surgery,Biotechnology

Reference46 articles.

1. Class prediction and discovery using gene expression data;D. K. Slonim

2. Deep Learning: Current State

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