“生物数学最新进展研讨会”系列报告

题    目：Integrating zero-inflation correction and transcriptional kinetics for single-cell transcriptomic analysis

主讲人：焦锋 教授

单    位：广州大学

时    间：2025年12月13日 17:00

腾讯ID：338-328-983

摘    要：Single-cell transcriptomic data exhibit pervasive zero inflation, while traditional models          either neglect this issue or fail to capture transcriptional burst-driven bimodality, restricting gene         regulatory studies. We developed a zero-inflated telegraph model that integrates technical zero           correction with the stochastic gene state-switching dynamics of the classical telegraph model.             Systematic validation was conducted using synthetic data, human scRNA-seq data from lupus and    breast cancer patients, and mouse embryonic stem cell smFISH/scRNA-seq data. The model showed  superior performance: it accurately fits mRNA distributions (including bimodal patterns), reliably        estimates transcriptional burst parameters while preventing overfitting, thus enables correction of      traditional models’ regulatory inference bias. It also outperforms traditional models and algorithms in detecting differentially expressed genes, with notable advantages in small samples, and identifies unique disease-related genes (e.g., LDLR, GZMB for lupus, FAIM2, VDR for breast cancer). This biologically interpretable and robust tool advances single-cell transcriptomic analysis, facilitating research on transcriptional regulatory dynamics and screening of disease therapeutic targets.

简    介：焦锋，教授，博士生导师，中国数学会理事，广东省计算数学学会副理事长。长期从事微分方程理论方法研究，并将其应用于基因转录的随机动力学、模型优化及相关数据分析领域。相关工作先后获评广东省自然科学奖二等奖、秦元勋青年数学奖、湖南省自然科学奖二等奖，是全国高校黄大年式教师团队核心成员（前5），广东省创新团队项目负责人。