A large number of DNA copy number alterations (CNAs) exist in human breast cancers, and thus characterizing the most frequent ones is key to advancing therapeutics because it is likely that these recu

NIAID Data Ecosystem40

An Integrated Approach to Uncover Driver Genes in Breast Cancer Methylation Genomes

乳腺癌驱动基因

甲基化基因组分析

Background Cancer cells typically exhibit large-scale aberrant methylation of gene promoters. Some of the genes with promoter methylation alterations play “driver” roles in tumorigenesis, whereas othe

NIAID Data Ecosystem50

Integration of transcript expression, copy number and LOH analysis of infiltrating ductal carcinoma of the breast: expression analysis. Homo sapiens

乳腺癌驱动基因

整合基因组学

Introduction: A major challenge in the interpretation of genomic profiling data generated from breast cancer samples is the identification of driver genes as distinct from bystander genes which do not

NIAID Data Ecosystem40

Driver genes for luminal breast cancer.

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