基于计算方法解析细胞调控图谱
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更新：2022-07-01 11:40:33
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特邀报告
报告开始：2022年07月23日 15:30 （Asia/Shanghai）
报告时间：20min
所在会议：[S5] 分会场5 » [S5-1] 单细胞组学技术开发与应用
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摘要
Human individual cells, as the basic biological units of our bodies, carry out their functions
through rigorous regulation of gene expression and exhibit heterogeneity among each other
in every human tissue. In addition to identify individual genes, one is often interested in how
multiple genes interact to form regulatory circuits and carry out cellular functions.
Combining massive omics data and leading-edge statistical modeling/machine learning
approaches, we have developed set of novel bioinformatic technologies to delineate the
and translational study.
through rigorous regulation of gene expression and exhibit heterogeneity among each other
in every human tissue. In addition to identify individual genes, one is often interested in how
multiple genes interact to form regulatory circuits and carry out cellular functions.
Combining massive omics data and leading-edge statistical modeling/machine learning
approaches, we have developed set of novel bioinformatic technologies to delineate the
regulatory map and characterize the functional genome in action globally during past years.
Here we will present our recent advances as well as their potential applications in clinicaland translational study.
关键字
细胞调控图谱; 单细胞多组学; 深度学习
报告人
高歌
研究员 北京大学实验室长期专注于生物信息新技术新方法开发，2016年至今，自主开发的十余个生物信息学新算法软件及数据库获外部有效访问14亿次，半数以上来自海外，跻身于国内自主开发最具国际影响力的生物信息技术行列；期间多篇研究论文入选ESI Highly Cited (Top 1%) Paper、中国生物信息学十大进展、中国生物信息学十大数据库、中国热点论文榜、Faculty 1000 Very Good Paper等，累计它引逾一万六千次。相关工作获得国内外同行认可，多次入选Clarivate/SCI全球高被引学者、Elsevier中国高被引学者(2020、2021)等。实验室当前研究聚焦开发新一代生物信息学方法与技术，通过整合挖掘多组学大数据，在单细胞水平精准构建、解析细胞调控图谱并探索其在生物医学方面的应用。
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