<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>sibscc.r-universe.dev</title><link>https://sibscc.r-universe.dev</link><description>Recent package updates in sibscc</description><generator>R-universe</generator><image><url>https://github.com/sibscc.png</url><title>R packages by sibscc</title><link>https://sibscc.r-universe.dev</link></image><lastBuildDate>Tue, 28 Apr 2026 12:39:17 GMT</lastBuildDate><item><title>[bioc] RGSEA 1.47.0</title><author>ccma@sibs.ac.cn (Chengcheng Ma)</author><description>Combining bootstrap aggregating and Gene set enrichment
analysis (GSEA), RGSEA is a classfication algorithm with high
robustness and no over-fitting problem. It performs well
especially for the data generated from different exprements.</description><link>https://github.com/r-universe/bioc/actions/runs/39112605971</link><pubDate>Tue, 28 Apr 2026 12:39:17 GMT</pubDate><r:package>RGSEA</r:package><r:version>1.47.0</r:version><r:status>success</r:status><r:repository>https://bioc.r-universe.dev</r:repository><r:upstream>https://github.com/bioc/RGSEA</r:upstream><r:article><r:source>RGSEA.Rnw</r:source><r:filename>RGSEA.pdf</r:filename><r:title>Introduction to RGSEA</r:title><r:created>2014-06-07 00:22:32</r:created><r:modified>2014-06-07 00:22:32</r:modified></r:article></item></channel></rss>