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Gene Expression Regulation, Neoplastic

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Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas.

Cell reports
Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these "hidden responders" may reveal responsive molecular states. We describe and evaluate a mach...

Identification of recurrent risk-related genes and establishment of support vector machine prediction model for gastric cancer.

Neoplasma
This study sought to investigate genes related to recurrent risk and establish a support vector machine (SVM) classifier for prediction of recurrent risk in gastric cancer (GC).Based on the gene expression profiling dataset GSE26253, feature genes th...

BioMuta and BioXpress: mutation and expression knowledgebases for cancer biomarker discovery.

Nucleic acids research
Single-nucleotide variation and gene expression of disease samples represent important resources for biomarker discovery. Many databases have been built to host and make available such data to the community, but these databases are frequently limited...

Electronic Health Record Phenotypes for Precision Medicine: Perspectives and Caveats From Treatment of Breast Cancer at a Single Institution.

Clinical and translational science
Precision medicine is at the forefront of biomedical research. Cancer registries provide rich perspectives and electronic health records (EHRs) are commonly utilized to gather additional clinical data elements needed for translational research. Howev...

Image-based surrogate biomarkers for molecular subtypes of colorectal cancer.

Bioinformatics (Oxford, England)
MOTIVATION: Whole genome expression profiling of large cohorts of different types of cancer led to the identification of distinct molecular subcategories (subtypes) that may partially explain the observed inter-tumoral heterogeneity. This is also the...