Unlocking the Potential of the CA2, CA7, and ITM2C Gene Signatures for the Early Detection of Colorectal Cancer: A Comprehensive Analysis of RNA-Seq Data by Utilizing Machine Learning Algorithms

Unlocking the Potential of the CA2, CA7, and ITM2C Gene Signatures for the Early Detection of Colorectal Cancer: A Comprehensive Analysis of RNA-Seq Data by Utilizing Machine Learning Algorithms

Colorectal cancer affects the colon or rectum and is a common global health issue, with 1.1 million new cases occurring yearly. The study aimed to identify gene signatures for the early detection of CRC using machine learning (ML) algorithms utilizing gene expression data. The TCGA-CRC and GSE50760...

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Bibliographic Details
Main Authors: Neha Shree Maurya, Sandeep Kushwaha, Ramesh Raju Vetukuri, Ashutosh Mani
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Genes
Subjects:
colorectal cancer
feature selection
machine learning
gene expression
gene signatures
correlation
Online Access:https://www.mdpi.com/2073-4425/14/10/1836

Internet

https://www.mdpi.com/2073-4425/14/10/1836

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