Combined High-Throughput Proteomics and Random Forest Machine-Learning Approach Differentiates and C...
Combined High-Throughput Proteomics and Random Forest Machine-Learning Approach Differentiates and Classifies Metabolic, Immune, Signaling and ECM Intra-Tumor Heterogeneity of Colorectal Cancer
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Switzerland: MDPI AG
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English
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Publisher
Switzerland: MDPI AG
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Colorectal cancer (CRC) is a frequent, worldwide tumor described for its huge complexity, including inter-/intra-heterogeneity and tumor microenvironment (TME) variability. Intra-tumor heterogeneity and its connections with metabolic reprogramming and epithelial-mesenchymal transition (EMT) were investigated with explorative shotgun proteomics comp...
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Combined High-Throughput Proteomics and Random Forest Machine-Learning Approach Differentiates and Classifies Metabolic, Immune, Signaling and ECM Intra-Tumor Heterogeneity of Colorectal Cancer
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TN_cdi_doaj_primary_oai_doaj_org_article_1d0e0d32178540e5b4c651ccb03c8f00
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_1d0e0d32178540e5b4c651ccb03c8f00
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ISSN
2073-4409
E-ISSN
2073-4409
DOI
10.3390/cells13161311
