Better than gene sequencing or quantitative amplification, proteomics tools allow the study
of tumor phenotype. Indeed, most current prognostic tests in cancer (carcinoembryonary …

Background Microarray technology is increasingly used to identify potential biomarkers for
cancer prognostics and diagnostics. Previously, we have developed the iterative Bayesian …

Carcinogenesis is a complex process with multiple genetic and environmental factors
contributing to the development of one or more tumors. Understanding the underlying …

Prognostic models for disease occurrence, tumor progression and survival are abundant for
most types of cancers. Physicians and cancer patients are utilizing these models to make …

Cancer is one of the leading cause of death, worldwide. Many believe that genomic data will
enable us to better predict the survival time of these patients, which will lead to better, more …

With the improvement of-omics and next-generation sequencing (NGS) methodologies,
along with the lowered cost of generating these types of data, the analysis of high …

Gene-expression profiling can be used to classify human tumors into molecular subtypes or
risk groups, representing potential future clinical tools for treatment prediction and …

Breast cancer (BRCA) is the primary cause of mortality among females globally. The
combination of advanced genomic analysis with proteomics characterization to construct a …

Background The classic central dogma in biology is the information flow from DNA to mRNA
to protein, yet complicated regulatory mechanisms underlying protein translation often lead …

Knowledge of transcription of the human genome might greatly enhance our understanding
of cancer. In particular, gene expression may be used to predict the survival of cancer …