There is an increasing demand to determine the clinical implication of experimental findings in molecular biomedical research. Survival (or failure time) analysis methodologies have been adapted to the analysis of genomics data to link molecular information with clinical outcomes of interest. Genome-wide molecular profiles have served as sources for discovery of predictive/prognostic biomarkers as well as therapeutic targets in the past decade. In this review, we overview currently available software, web applications, and databases specifically developed for survival analysis in genomics research and discuss issues in assessing clinical utility of molecular features derived from genomic profiling.
%0 Journal Article
%1 Chen:2014:Hum-Genomics:25421963
%A Chen, X
%A Sun, X
%A Hoshida, Y
%D 2014
%J Hum Genomics
%K SHOULDREAD cancer-research fulltext review software survival
%P 21-21
%R 10.1186/s40246-014-0021-z
%T Survival analysis tools in genomics research
%U https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4246473/
%V 8
%X There is an increasing demand to determine the clinical implication of experimental findings in molecular biomedical research. Survival (or failure time) analysis methodologies have been adapted to the analysis of genomics data to link molecular information with clinical outcomes of interest. Genome-wide molecular profiles have served as sources for discovery of predictive/prognostic biomarkers as well as therapeutic targets in the past decade. In this review, we overview currently available software, web applications, and databases specifically developed for survival analysis in genomics research and discuss issues in assessing clinical utility of molecular features derived from genomic profiling.
@article{Chen:2014:Hum-Genomics:25421963,
abstract = {There is an increasing demand to determine the clinical implication of experimental findings in molecular biomedical research. Survival (or failure time) analysis methodologies have been adapted to the analysis of genomics data to link molecular information with clinical outcomes of interest. Genome-wide molecular profiles have served as sources for discovery of predictive/prognostic biomarkers as well as therapeutic targets in the past decade. In this review, we overview currently available software, web applications, and databases specifically developed for survival analysis in genomics research and discuss issues in assessing clinical utility of molecular features derived from genomic profiling.},
added-at = {2017-10-22T13:07:38.000+0200},
author = {Chen, X and Sun, X and Hoshida, Y},
biburl = {https://www.bibsonomy.org/bibtex/266a206cb89ada94bbb88ec2f07976a9a/marcsaric},
description = {Survival analysis tools in genomics research},
doi = {10.1186/s40246-014-0021-z},
interhash = {cca66d24015abb085311fe1f84e981ff},
intrahash = {66a206cb89ada94bbb88ec2f07976a9a},
journal = {Hum Genomics},
keywords = {SHOULDREAD cancer-research fulltext review software survival},
month = nov,
pages = {21-21},
pmid = {25421963},
timestamp = {2017-10-22T13:07:38.000+0200},
title = {Survival analysis tools in genomics research},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4246473/},
volume = 8,
year = 2014
}