High-Throughput Omics and Statistical Learning Integration for the Discovery and Validation of Novel Diagnostic Signatures in Colorectal Cancer
The advancement of bioinformatics and machine learning has facilitated the discovery and validation of omics-based biomarkers. This study employed a novel approach combining multi-platform transcriptomics and cutting-edge algorithms to introduce novel signatures for accurate diagnosis of colorectal...
Main Authors: | Nguyen Phuoc Long, Seongoh Park, Nguyen Hoang Anh, Tran Diem Nghi, Sang Jun Yoon, Jeong Hill Park, Johan Lim, Sung Won Kwon |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-01-01
|
Series: | International Journal of Molecular Sciences |
Subjects: | |
Online Access: | http://www.mdpi.com/1422-0067/20/2/296 |
Similar Items
-
An Integrative Data Mining and Omics-Based Translational Model for the Identification and Validation of Oncogenic Biomarkers of Pancreatic Cancer
by: Nguyen Phuoc Long, et al.
Published: (2019-01-01) -
Effects of <i>β</i>-Cryptoxanthin on Improvement in Osteoporosis Risk: A Systematic Review and Meta-Analysis of Observational Studies
by: Sun Jo Kim, et al.
Published: (2021-02-01) -
Molecular and Metabolic Phenotyping of Hepatocellular Carcinoma for Biomarker Discovery: A Meta-Analysis
by: Nguyen Hoang Anh, et al.
Published: (2023-10-01) -
Multi-Omic Approaches in Colorectal Cancer beyond Genomic Data
by: Emilia Sardo, et al.
Published: (2022-01-01) -
Proteomic Profiling and Biomarker Discovery in Colorectal Liver Metastases
by: Geoffrey Yuet Mun Wong, et al.
Published: (2022-05-01)