Cargando…
Using Machine Learning Methods to Study Colorectal Cancer Tumor Micro-Environment and Its Biomarkers
Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide, and the identification of biomarkers can improve early detection and personalized treatment. In this study, RNA-seq data and gene chip data from TCGA and GEO were used to explore potential biomarkers for CRC. The SMOTE method was...
Autores principales: | Wei, Wei, Li, Yixue, Huang, Tao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10342679/ https://www.ncbi.nlm.nih.gov/pubmed/37446311 http://dx.doi.org/10.3390/ijms241311133 |
Ejemplares similares
-
Staging of colorectal cancer using lipid biomarkers and machine learning
por: Krishnan, Sanduru Thamarai, et al.
Publicado: (2023) -
Identifying MicroRNA Markers That Predict COVID-19 Severity Using Machine Learning Methods
por: Ren, Jingxin, et al.
Publicado: (2022) -
Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods
por: Li, ZhanDong, et al.
Publicado: (2022) -
Integrative Analysis of Biomarkers Through Machine Learning Identifies Stemness Features in Colorectal Cancer
por: Wei, Ran, et al.
Publicado: (2021) -
Early lung cancer diagnostic biomarker discovery by machine learning methods
por: Xie, Ying, et al.
Publicado: (2020)