Analysis of Early Mouse Cerebellar Neuron Developmental Control Pathways

早期小鼠小脑神经元发育控制通路分析

• 批准号: 7665549
• 负责人: WILLIAM J BOSL
• 金额: $ 22万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7665549
• 关键词: Adopted; Biochemical; Biochemical Pathway; Candidate Disease Gene; Cell Cycle Progression; Cell Cycle Regulation; Cell Surface Proteins; Cells; Characteristics; Complex; Computer Simulation; Computing Methodologies; Cytokinesis; Data; Data Sources; Databases; Defect; Detection; Development; Disease; Drug Delivery Systems; Elements; Epigenetic Process; Eukaryota; Evolution; Exhibits; Financial compensation; Fuzzy Logic; Gene Deletion; Gene Expression; Gene Proteins; Generations; Genes; Genetic; Genetic Crosses; Genome; Genomics; Goals; Growth; High temperature of physical object; Immune system; Knock-out; Lead; Life; Literature; Malignant Neoplasms; Measurement; Measures; Medical; Medicine; Methods; Microarray Analysis; Mitosis; Mitotic; Modeling; Modification; Molecular Profiling; Mus; Mutation; Neurons; Organism; Paper; Pathway interactions; Pattern; Pharmaceutical Preparations; Play; Protein Databases; Publications; Publishing; Regulation; Role; Saccharomycetales; Signal Pathway; Source; Spectrum Analysis; Structure; System; Systems Biology; Techniques; Testing; Therapeutic; Time; base; cancer cell; cellular imaging; cold temperature; deletion analysis; design; disorder control; epigenetic variation; gene interaction; insight; mutant; overexpression; pathogen; practical application; programs; research study; response; simulation; therapy development

DESCRIPTION (provided by applicant): The ability of cells and organisms to generate heritable alternative strategies through genetic or epigenetic variations is not well understood and is a central issue in evolution and disease control. The contribution of network complexity to evolvability of new cellular mechanisms is directly relevant to a variety of medical concerns. For example, cancer cells have incredible abilities to escape treatments that are intended to block their growth. Pathogens are known to use epigenetic and genetic modifications to rapidly switch expression of cell-surface proteins to escape detection by the immune system. An important task for quantitative genomic medicine is to characterize the adaptive response of cells to perturbations by drugs or mutation, then to quantify them with models and predict the patterns of adaptation. A systems approach will be adopted to characterize the complex genetic or epigenetic changes in budding yeast cells in response to perturbations of the mitotic exit network. The mitotic exit network (MEN) is a complicated regulatory network that interacts with several other important pathways to control the timing of mitotic exit and cytokinesis. The fundamental goal is to determine if characteristic patterns and organizational principles are exhibited in suppressors when key genes are deleted from the MEN pathway. Genetic crosses, live cell imaging, and microarray expression measurements will be used to characterize adaptations. Then data from recent publications will be integrated with corroborating data from several sources to build computational models of the MEN and adaptations, which will be analyzed and compared quantitatively to discover patterns. This may provide insights into how network complexity contributes to the activation of new cellular mechanisms and may have practical applications for predicting the possible response of cells to targeted drug treatments.

描述（由申请人提供）：细胞和生物体通过遗传或表观遗传变异产生可遗传替代策略的能力尚未得到很好的理解，并且是进化和疾病控制的中心问题。网络复杂性对新细胞机制的可进化性的贡献与各种医学问题直接相关。例如，癌细胞具有令人难以置信的能力，可以逃避旨在阻止其生长的治疗。众所周知，病原体利用表观遗传和遗传修饰迅速改变细胞表面蛋白的表达，以逃避免疫系统的检测。定量基因组医学的一项重要任务是描述细胞对药物或突变扰动的适应性反应，然后用模型对其进行量化并预测适应模式。