<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Single-Cell Transcriptomics | Feiying Chen</title><link>https://cfy2yue.github.io/tags/single-cell-transcriptomics/</link><atom:link href="https://cfy2yue.github.io/tags/single-cell-transcriptomics/index.xml" rel="self" type="application/rss+xml"/><description>Single-Cell Transcriptomics</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sun, 07 Jun 2026 00:00:00 +0000</lastBuildDate><image><url>https://cfy2yue.github.io/media/icon_hu_1c0e9cb08cfb822a.png</url><title>Single-Cell Transcriptomics</title><link>https://cfy2yue.github.io/tags/single-cell-transcriptomics/</link></image><item><title>Perturbation Biology and AI Virtual Cells</title><link>https://cfy2yue.github.io/projects/perturbation-biology/</link><pubDate>Sun, 07 Jun 2026 00:00:00 +0000</pubDate><guid>https://cfy2yue.github.io/projects/perturbation-biology/</guid><description>&lt;p&gt;I am interested in models that connect perturbations, cellular state transitions, and phenotype-level responses. Current directions include single-cell foundation model pretraining, post-training for perturbation response prediction, model deployment for biological workflows, and AI virtual cell frameworks for tumor microenvironment analysis.&lt;/p&gt;</description></item></channel></rss>