1. A hierarchical clustering approach for colorectal cancer molecular subtypes identification from gene expression data
    Shivangi Raghav et al, 2024, Intelligent Medicine CrossRef
  2. Omada: robust clustering of transcriptomes through multiple testing
    Sokratis Kariotis et al, 2024, GigaScience CrossRef
  3. Multiplexed Liquid Chromatography-Multiple Reaction Monitoring Mass Spectrometry Quantification of Cancer Signaling Proteins
    Yi Chen et al, 2017, Proteomics for Drug Discovery CrossRef
  4. Methylome and transcriptome analyses reveal insights into the epigenetic basis for the good survival of hypomethylated ER-positive breast cancer subtype
    Xiao-Qiong Chen et al, 2020, Clinical Epigenetics CrossRef
  5. Cluster analysis on high dimensional RNA-seq data with applications to cancer research - An evaluation study
    Linda Vidman et al, 2019, PLOS ONE CrossRef
  6. Aberrant methylation patterns in colorectal cancer: a meta-analysis
    Danielle Fernandes Durso et al, 2017, Oncotarget CrossRef
  7. Comparison of Methods for Feature Selection in Clustering of High-Dimensional RNA-Sequencing Data to Identify Cancer Subtypes
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  8. An efficient hybrid methodology for detection of cancer-causing gene using CSC for micro array data
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  9. Identification of Distinct Molecular Patterns and a Four-Gene Signature in Colon Cancer Based on Invasion-Related Genes
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  10. LncRNA UCA1, Upregulated in CRC Biopsies and Downregulated in Serum Exosomes, Controls mRNA Expression by RNA-RNA Interactions
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  11. A Metaheuristic Technique for Cluster-Based Feature Selection of DNA Methylation Data for Cancer
    Noureldin Eissa et al, 2023, Computers, Materials & Continua CrossRef
  12. An Integrated Approach for Identifying Molecular Subtypes in Human Colon Cancer Using Gene Expression Data
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  13. Identification of key differentially expressed MicroRNAs in cancer patients through pan-cancer analysis
    Yu Hu et al, 2018, Computers in Biology and Medicine CrossRef
  14. In Silico Gene Prioritization Highlights the Significance of Bone Morphogenetic Protein 4 (BMP4) Promoter Methylation across All Methylation Clusters in Colorectal Cancer
    Daša Jevšinek Skok et al, 2023, International Journal of Molecular Sciences CrossRef
  15. (‐)‐Epigallocatechin‐3‐gallate and atorvastatin treatment down‐regulates liver fibrosis‐related genes in non‐alcoholic fatty liver disease
    Le Ying et al, 2017, Clinical and Experimental Pharmacology and Physiology CrossRef
  16. Robust Significance Analysis of Microarrays by Minimumβ-Divergence Method
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  17. Stratification of Breast Cancer by Integrating Gene Expression Data and Clinical Variables
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  18. Analysis of 5-Methylcytosine Regulators and DNA Methylation-Driven Genes in Colon Cancer
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