The identification of genomic, molecular and clinical markers predictive of patient survival is
important for developing personalized disease prevention, diagnostic and treatment …

Motivation Identification of genomic, molecular and clinical markers prognostic of patient
survival is important for developing personalized disease prevention, diagnostic and …

Identifying relevant genomic features that can act as prognostic markers for building
predictive survival models is one of the central themes in medical research, affecting the …

We present DoSurvive, a user-friendly survival analysis web tool and a cancer prognostic
biomarker centered database. DoSurvive is the first database that allows users to perform …

Multiple omic profiles have been generated for many cancer types; however, comprehensive
assessment of their prognostic values across cancers is limited. We conducted a pan-cancer …

Detection of prognostic factors associated with patients' survival outcome helps gain insights
into a disease and guide treatment decisions. The rapid advancement of high-throughput …

Abstract High-throughput “omics” data, including genomic, transcriptomic, and epigenetic
data, have become increasingly produced and have contributed in recent years to the …

Biomedical datasets, which consist of molecular profiling data from patients in combination
with clinical parameters, pose complex statistical challenges due to their inherent …

Survival analysis is a branch of statistics that deals with both the tracking of time and the
survival status simultaneously as the dependent response. Current comparisons of survival …

The genomics era has yielded great advances in the understanding of cancer biology. At the
same time, the immense complexity of the cancer genome has been revealed, as well as a …