scRL: Utilizing Reinforcement Learning to Evaluate Fate Decisions in Single-Cell Data

Single-cell RNA sequencing now profiles whole transcriptomes for hundreds of thousands of cells, yet existing trajectory-inference tools rarely pinpoint where and when fate decisions are made. We present single-cell reinforcement learning (scRL), an actor–critic framework that recasts differentiatio...

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Bibliographic Details

Published in:	Biology
Main Authors:	Zeyu Fu, Chunlin Chen, Song Wang, Junping Wang, Shilei Chen
Format:	Article
Language:	English
Published:	MDPI AG 2025-06-01
Subjects:	single–cell reinforcement learning actor–critic fate decisions trajectory inference dimensionality reduction
Online Access:	https://www.mdpi.com/2079-7737/14/6/679