报告题目：Optimal control nodes in disease-perturbed networks as targets for combination therapy
报告时间：2019年12月13日下午16:30
报告地点：吉林大学中心校区计算机大楼A521
报告人：高琳
报告人简介：
高琳，女，博士，西安电子科技大学计算机科学与技术学院二级教授。西安电子科技大学学术委员会委员。计算机学会“生物信息专委员会 ”副主任，人工智能学会“生物信息学与人工生命专委会”副主任，运筹学会“计算生物信息学分会”常务理事。在生物数据挖掘与分析、模式识别与机器学习、图论与组合优化方面进行了长期研究，承担国家自然科学基金重点项目、重大研究计划和面上等项目，参与科技部“精准医疗”重点专项。在Nature Communications, Advanced Science, Nucleic Acids Research, Bioinformatics, Briefings in Bioinformatics等期刊发表论文100余篇。
报告内容简介：
Most combination therapies are developed based on targets of existing drugs, which only represent a small portion of the human proteome. We introduce a network controllability-based method, OptiCon, for de novo identification of synergistic regulators as candidates for combination therapy. These regulators jointly exert maximal control over deregulated genes but minimal control over unperturbed genes in a disease. Using data from three cancer types, we show that 68% of predicted regulators are either known drug targets or have a critical role in cancer development. Predicted regulators are depleted for known proteins associated with side effects. Predicted synergy is supported by disease-specific and clinically relevant synthetic lethal interactions and experimental validation. A significant portion of genes regulated by synergistic regulators participate in dense interactions between co-regulated subnetworks and contribute to therapy resistance. OptiCon represents a general framework for systemic and de novo identification of synergistic regulators underlying a cellular state transition.
主办单位：
吉林大学计算机科学与技术学院
吉林大学软件学院
吉林大学计算机科学技术研究所
符号计算与知识工程教育部重点实验室
吉林大学国家级计算机实验教学示范中心
吉林大学肿瘤系统生物学科学家工作室
吉林大学中日联谊医院肿瘤系统生物学实验室
CCF长春、YOCSEF长春、CCF吉大、吉林省计算机学会
