Systems Biology of Cell Decision Processes

细胞决策过程的系统生物学

基本信息

批准号：
7479966
负责人：
PETER Karl SORGER
金额：
$ 4.81万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2003
资助国家：
美国
起止时间：
2003-09-01 至 2008-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7479966
关键词：
Accountability Accounting Address Adopted Algorithms Amino Acid Sequence Animals Annual Reports Apoptosis Apoptotic Appendix Area Artificial Intelligence Attention Authorship Automation Award BCL2L11 gene Belief Binding Biochemical Biochemistry Bioinformatics Biological Biological Assay Biological Models Biological Phenomena Biological Process Biological Sciences Biology Biomedical Engineering Boxing Budgets Cancer Center Cell Extracts Cell model Cell physiology Cells Cellular Structures Cellular biology Chemical Engineering Chemical Structure Chemicals Child Classification Code Collaborations Color Commit Communities Complement Complex Computational Biology Computer software Computers Computing Methodologies Core Facility Data Data Analyses Databases Detection Development Devices Discipline Disputes Doctor of Philosophy Drug Formulations Drug Industry Education Education and Outreach Educational Curriculum Educational process of instructing Electrical Engineering Electronics Engineering Ensure Equilibrium Equipment Event Evolution Experimental Models Facility Construction Funding Category Faculty Feedback Figs - dietary Foundations Funding Future Gene Proteins Genes Genetic Genetic Transcription Genome Components Goals Grant Gray unit of radiation dose Head High Performance Computing High Pressure Liquid Chromatography Historically Black Colleges and Universities Home environment Human Human Resources Hybrids Image Individual Informatics Information Theory Institutes Institution Interdisciplinary Study Internet Interruption Investments Joints Knowledge Label Lead Leadership Learning Letters Life Link Mammalian Cell Manuals Mass Spectrum Analysis Mathematics Measurement Measures Mechanics Medical Device Metabolic Methods Microfluidics Microscopy Mining Minority-Serving Institution Mission Modeling Modification Molecular Molecular Biology Molecular Genetics Molecular Profiling Molecular and Cellular Biology Monitor Mus NCI Center for Cancer Research Nature Numbers Operative Surgical Procedures Outcome Outcomes Research Paper Pathway Analysis Pathway interactions Peptide Sequence Determination Performance Phase Phosphorylation Play Policies Positioning Attribute Principal Investigator Process Productivity Property Protein Analysis Proteins Proteomics Protons Publications Purpose Range Reaction Reliance Research Research Activity Research Personnel Research Project Grants Research Training Resource Allocation Resources Risk Role Route Running Schools Science Scientist Seeds Semiconductors Series Services Signal Transduction Signaling Molecule Soaps Source Specific qualifier value Students Supervision Support of Research System Systems Biology Techniques Technology Testing Time TimeLine To specify Training Training Programs Transgenic Organisms Underrepresented Minority United States National Institutes of Health Visit Work abstracting anticancer research base chemical reaction college computer based statistical methods computer science computerized data processing concept data mining data modeling design desire drug discovery experience fluid flow forging fundamental research instrument instrumentation interest intracellular protein transport member microsystems molecular modeling network models novel novel strategies open source outreach outreach program programs protein transport research facility research study response sensor size success systems research technology development tool virtual

项目摘要

The remarkable complexity of biological systems demands a systematic approach to their analysis. The goal of this proposal is to establish an MIT Center of Excellence in Cell Decision Processes (CDP) around an interdisciplinary team of cell biologists, computer scientists and microsystems engineers tackling the systems biology of protein networks and signal transduction in mammalian cells. The basic hypothesis of the CDP Center is that understanding cell decision processes requires the development of network models that combine quantitative rigor with molecular detail. These models will be hybrids containing highly specific representations of critical reactions and abstract representations of the system as a whole. Effective models will endure and capture the accumulation of knowledge over time in a rigorous and portable format. The CDP Center will follow a research paradigm that links systematic experiments and numerical modeling in a four-step feedback loop of manipulation-measurement-mining and modeling. The biological focus of the Center will be the signaling events that control apoptosis. The measurement of protein concentrations, modification state and activity will be undertaken for signaling molecules at many points in the apoptotic network. The measurements will then be analyzed using several modeling approaches ranging from highly specified to highly abstract. To collect sufficient data for systematic modeling, the CDP Center will automate and standardize biochemical methods, develop compact array-based assays and design novel microfabricated devices with integrated microfluidics and label-free sensors. To organize and systematize the data, inforrnatic methods will be developed that support rigorous approaches to inference. Finally, physico-chemical, structure-systems and Bayesian models will be used to generate biological hypothesis for experimental verification. The research activities of the CDP Center will be complemented by graduate and undergraduate education and by an outreach program targeted at the scientific community in general and minority-serving institutions in particular

生物系统极其复杂，需要采用系统的方法进行分析。该提案的目标是建立麻省理工学院细胞决策过程卓越中心（CDP）由细胞生物学家、计算机科学家和微系统工程师组成的跨学科团队围绕哺乳动物细胞中蛋白质网络和信号转导的系统生物学。基本假设为 CDP中心认为理解细胞决策过程需要开发网络模型将定量严谨性与分子细节结合起来。这些模型将是包含高度特异性的混合体关键反应的表示和整个系统的抽象表示。有效模型将以严格且可移植的格式承受并捕捉随着时间的推移而积累的知识。 CDP中心将遵循将系统实验和数值模拟联系起来的研究范式。在操纵-测量-挖掘和建模的四步反馈循环中进行建模。生物的该中心的重点将是控制细胞凋亡的信号事件。蛋白质的测定信号分子的浓度、修饰状态和活性将在许多点进行凋亡网络。然后将使用多种建模方法对测量结果进行分析从高度具体到高度抽象。为了收集足够的数据进行系统建模，CDP 中心将实现自动化和标准化生化方法，开发基于紧凑阵列的测定并设计新型微加工设备集成微流体和无标记传感器。为了组织和系统化数据，信息方法将开发支持严格的推理方法。最后，物理化学、结构系统和贝叶斯模型将用于生成生物学假设以进行实验验证。 CDP中心的研究活动将得到研究生和本科生的补充教育和针对整个科学界和少数族裔服务的外展计划特别是机构