NetClass: An R-package for network based, integrative biomarker signature discovery

20Citations
Citations of this article
98Readers
Mendeley users who have this article in their library.

Abstract

In the past years, there has been a growing interest in methods that incorporate network information into classification algorithms for biomarker signature discovery in personalized medicine. The general hope is that this way the typical low reproducibility of signatures, together with the difficulty to link them to biological knowledge, can be addressed. Complementary to these efforts, there is an increasing interest in integrating different data entities (e.g. gene and miRNA expressions) into comprehensive models. To our knowledge, R-package netClass is the first software that addresses both, network and data integration. Besides several published approaches for network integration, it specifically contains our recently published stSVM method, which allows for additional integration of gene and miRNA expression data into one predictive classifier. © The Author 2013. Published by Oxford University Press.

Cite

CITATION STYLE

APA

Cun, Y., & Fröhlich, H. (2014). NetClass: An R-package for network based, integrative biomarker signature discovery. Bioinformatics, 30(9), 1325–1326. https://doi.org/10.1093/bioinformatics/btu025

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free