报告时间：2017年11月13日（星期一）上午9:00 – 11:00

报告地点：知新楼B座936

报告人：苏正昌（教授）

报告人简介：阿拉巴马大学伯明翰分校生物物理学和生理学博士、美国橡树岭国家实验室计算生物学博士后，先后在美国佐治亚大学、北卡罗来纳大学夏洛特分校工作，在国内担任宁夏回族自治区特聘专家、宁夏大学兼职教授。研究领域主要包括（1）原核基因组转录因子结合位点预测方法研究；（2）运用RNA-seq技术对细菌转录组的复杂性分析研究；（3）通过多个ChIP-seq数据综合分析预测真核生物中顺式调控因子的研究；（4）通过单细胞转录组分析，推断转录调控网络与细胞命运/类型决定机制的研究。

Title：Understanding gene regulation at single cell resolution

Abstract：The recent advance of single-cell technologies has provided an unprecedented opportunity to bring new insights into many complex biological phenomena. We have explored the gene expression regulation using datasets generated by single-cell techniques in three aspects. First, we analyzed a large-scale gene expression dataset measured in individual cells throughout the embryogenesis of C. elegans in a nearly continuous time-scale. Second, we developed a novel clustering algorithm named SNN-Cliq that utilizes the shared nearest neighbor and graph-theoretic partitioning techniques. Our algorithm has the superiority of handling high-dimensional noisy data. Last, using an RNA-Seq technique, we profiled transcriptomes in 51 yeast cells from three treatments. We found that the transcription variation, or noise, shows distinct features under different treatments for certain functional gene modules and regulatory pathways. Our results also suggest that transcriptional noise is subject to regulation in response to environmental stresses.