Colorectal Cancer Prediction Based on Weighted Gene Co-Expression Network Analysis and Variational Auto-Encoder

Colorectal Cancer Prediction Based on Weighted Gene Co-Expression Network Analysis and Variational Auto-Encoder

An effective feature extraction method is key to improving the accuracy of a prediction model. From the Gene Expression Omnibus (GEO) database, which includes 13,487 genes, we obtained microarray gene expression data for 238 samples from colorectal cancer (CRC) samples and normal samples. Twelve gen...

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Bibliographic Details
Main Authors: Dongmei Ai, Yuduo Wang, Xiaoxin Li, Hongfei Pan
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Biomolecules
Subjects:
weighted gene co-expression network analysis
variational autoencoder
colorectal cancer
hub genes
classifier
Online Access:https://www.mdpi.com/2218-273X/10/9/1207

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