Pages that link to "Q41557019"

The following pages link to Identification of a multi-cancer gene expression biomarker for cancer clinical outcomes using a network-based algorithm (Q41557019):

Displaying 30 items.

• The Matricellular Receptor LRP1 Forms an Interface for Signaling and Endocytosis in Modulation of the Extracellular Tumor Environment (Q26776179) (← links)
• Integration and comparison of different genomic data for outcome prediction in cancer. (Q31013326) (← links)
• The prognostic potential of alternative transcript isoforms across human tumors (Q37185523) (← links)
• Probing the prostate tumour microenvironment II: Impact of hypoxia on a cell model of prostate cancer progression. (Q37716544) (← links)
• Cancer Markers Selection Using Network-Based Cox Regression: A Methodological and Computational Practice. (Q39631395) (← links)
• Verification and characterization of an alternative low density lipoprotein receptor-related protein 1 splice variant. (Q41001561) (← links)
• Identification of LRP-1 as an endocytosis and recycling receptor for β1-integrin in thyroid cancer cells. (Q45907437) (← links)
• Highly preserved consensus gene modules in human papilloma virus 16 positive cervical cancer and head and neck cancers. (Q47548799) (← links)
• Genes and functions from breast cancer signatures. (Q52560707) (← links)
• Identifying statistically significant combinatorial markers for survival analysis. (Q52561813) (← links)
• LYL1 gene amplification predicts poor survival of patients with uterine corpus endometrial carcinoma: analysis of the Cancer genome atlas data. (Q52715015) (← links)
• RNA Biomarkers: Frontier of Precision Medicine for Cancer. (Q54955356) (← links)
• LRP1 expression in colon cancer predicts clinical outcome. (Q55004772) (← links)
• Methylation-to-Expression Feature Models of Breast Cancer Accurately Predict Overall Survival, Distant-Recurrence Free Survival, and Pathologic Complete Response in Multiple Cohorts. (Q55084135) (← links)
• The role of glycosyltransferase enzyme GCNT3 in colon and ovarian cancer prognosis and chemoresistance. (Q55101661) (← links)
• A data-driven, knowledge-based approach to biomarker discovery: application to circulating microRNA markers of colorectal cancer prognosis. (Q55166178) (← links)
• Cross-cancer Prediction: A Novel Machine Learning Approach to Discover Molecular Targets for Development of Treatments for Multiple Cancers (Q58579184) (← links)
• Prognostic Gene Discovery in Glioblastoma Patients using Deep Learning (Q61800524) (← links)
• EMT network-based feature selection improves prognosis prediction in lung adenocarcinoma (Q61805560) (← links)
• An Ensemble Strategy to Predict Prognosis in Ovarian Cancer Based on Gene Modules (Q64092981) (← links)
• Identifying cancer prognostic modules by module network analysis (Q64255138) (← links)
• Systems Biology Approaches to Investigate Genetic and Epigenetic Molecular Progression Mechanisms for Identifying Gene Expression Signatures in Papillary Thyroid Cancer. (Q64927548) (← links)
• Network Properties of Cancer Prognostic Gene Signatures in the Human Protein Interactome (Q89944347) (← links)
• Overall survival prediction of non-small cell lung cancer by integrating microarray and clinical data with deep learning (Q90317181) (← links)
• Glycolysis gene expression profilings screen for prognostic risk signature of hepatocellular carcinoma (Q91603548) (← links)
• Sex-biased differences in the correlation between epithelial-to-mesenchymal transition-associated genes in cancer cell lines (Q91739199) (← links)
• Wx: a neural network-based feature selection algorithm for transcriptomic data (Q92035428) (← links)
• Integrative Analysis of Cancer Omics Data for Prognosis Modeling (Q92570530) (← links)
• Salivary Extracellular Vesicle-Associated exRNA as Cancer Biomarker (Q93080687) (← links)
• Transcriptome analysis uncovers the diagnostic value of miR-192-5p/HNF1A-AS1/VIL1 panel in cervical adenocarcinoma (Q100464649) (← links)