Proteomic data provide a direct readout of protein function, thus constituting an information-
rich resource for prognostic and predictive modeling. However, protein array data may not …

Personalized (patient-specific) approaches have recently emerged with a precision
medicine paradigm that acknowledges the fact that molecular pathway structures and …

Discovery of robust diagnostic or prognostic biomarkers is a key to optimizing therapeutic
benefit for select patient cohorts-an idea commonly referred to as precision medicine. Most …

Background The analysis of integrated multi-omics data enables the identification of disease-
related biomarkers that cannot be identified from a single omics profile. Although protein …

Identifying perturbed pathways at an individual level is important to discover the causes of
cancer and develop individualized custom therapeutic strategies. Though prognostic gene …

Background In 2016, it is estimated that there will be 62,700 new cases of kidney cancer in
the United States, and 14,240 patients will die from the disease. Because the incidence of …

Gene expression profiling has identified cancer prognostic and predictive signatures with
superior performance to conventional histopathological or clinical parameters …

Gene expression measurements have successfully been used for building prognostic
signatures, ie for identifying a short list of important genes that can predict patient outcome …

Heterogeneity in terms of tumor characteristics, prognosis, and survival among cancer
patients has been a persistent problem for many decades. Currently, prognosis and …

Identifying patient-specific prognostic biomarkers is of critical importance in developing
personalized treatment for clinically and molecularly heterogeneous diseases such as …