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Signalling network: from regulation to cancer development
Speaker:
Dr. Qinghua Cui
National Research Council Canada
Time: 2-3pm, Wednesday May 23
Location: Room 610, New Life Science Building, Peking University
Abstract:
Genes are not independent but interact with each other to form complex cellular networks. Systematic analysis in network level to biological questions becomes increasingly important over the past few years. Among these cellular networks, signaling network represents one of the most important ones because its important roles in many biological processes and diseases. Quantitative and qualitative analysis to cellular signaling networks can improve our understanding to biological processes and diseases. Here, we manually constructed a human signaling network that contains 1634 nodes and 5089 interactions, which is the most comprehensive human signaling network to our knowledge. In this talk, I will introduce three topics of my signaling network research: microRNAs’ regulation in a signaling network, cross species gene expression diversity of a signaling network, and an oncogenic signaling. For microRNAs’ regulation, we found that microRNAs prefer to regulate downstream components, positively linked network motifs, highly linked scaffolds etc, and avoid regulating upstream components and common components of cellular machines. For cross species gene expression diversity, we uncovered the co-evolution modes of network genes, we also found that different types of interactions contribute differently to the co-evolution of gene expression. Among these three types of interactions in signaling network, inhibition contributes most. Signaling hubs and functional modules have lower gene expression diversity. For oncogenic signaling map, we found that cancer mutation and methylation genes are enriched in positive and negative regulatory loops. Respectively. We identified an oncogenic signaling map, which was decomposed into 12 topological regions or oncogenic signaling blocks including two oncogenic signaling addicted blocks. Aggravating collaborations of the genes were found within and between the blocks, especially between the two oncogenic signaling addicted blocks. These conclusions are further enforced by benchmarking two datasets derived from the mutation analysis of the NCI-60 cancer cell lines and the genome-wide sequencing of 22 tumor samples. Furthermore, the mutation genes in the network can be used to discover cancer-associated genes and novel biomarkers. In summary, our work provides important evidences for microRNA regulation mechanisms, gene expression evolution, and cancer development.
Bio:
崔庆华博士1999年本科毕业于河北工业大学机械电子工程系，同年考入河北工业大学机器人与自动化研究所攻读硕士学位，从事机器人视觉的研究工作，２００２年取得工学硕士学位之后，考入中科院自动化所攻读博士学位，开始了生物信息学的研究工作。在2005年获得博士学位之后，崔博士加入加拿大国家研究委员会生物技术研究所做博士后，继续从事生物信息学和计算生物学的研究工作。在近5年来的生物信息学研究工作中，崔博士的研究兴趣涉及了基因组学、蛋白质组学以及系统生物学等领域，他的一些工作发表在了Molecular Systems Biology，Trends in Genetics，Bioinformatics，BMC Bioinformatics，以及BBRC等期刊上。崔博士当前的研究兴趣主要是结合基因组、蛋白质组、生物网络等数据和模式识别等分析方法的生物学问题研究。
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