報告題目：Optimal control nodes in disease-perturbed networks as targets for combination therapy
報告時間：2019年12月13日下午16:30
報告地點：伟德国际BETVlCTOR中心校區計算機大樓A521
報告人：高琳
報告人簡介：
高琳，女，博士，西安電子科技大學伟德国际BETVlCTOR二級教授。西安電子科技大學學術委員會委員。計算機學會“生物信息專委員會 ”副主任，人工智能學會“生物信息學與人工生命專委會”副主任，運籌學會“計算生物信息學分會”常務理事。在生物數據挖掘與分析、模式識别與機器學習、圖論與組合優化方面進行了長期研究，承擔國家自然科學基金重點項目、重大研究計劃和面上等項目，參與科技部“精準醫療”重點專項。在Nature Communications, Advanced Science, Nucleic Acids Research, Bioinformatics, Briefings in Bioinformatics等期刊發表論文100餘篇。
報告内容簡介：
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.
主辦單位：
伟德国际BETVlCTOR
伟德国际BETVlCTOR軟件學院
伟德国际BETVlCTOR計算機科學技術研究所
符号計算與知識工程教育部重點實驗室
伟德国际BETVlCTOR國家級計算機實驗教學示範中心
伟德国际BETVlCTOR腫瘤系統生物學科學家工作室
伟德国际BETVlCTOR中日聯誼醫院腫瘤系統生物學實驗室
CCF長春、YOCSEF長春、CCF吉大、吉林省計算機學會
