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中文摘要
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在过去的几年里,强大的新方法已经被设计出来,使研究人员能够同时研究整个基因组表达的动态。 理论上,这些潜在的大量数据使得能够解剖控制细胞中基因表达模式和节奏的复杂遗传网络。 拟议的工作的目标是开发一个系统分析的全基因组表达谱。 我们的目的是从基因表达数据中推断调控网络,并用实验结果验证这些程序。 为此,该项目将整合以下工作:系统建模和大型网络的可视化,模型系统的实验以及数据库和生物信息学工具的开发。我们的战略,确定基因型与复杂的表型是使用正常和功能失活系统的时间序列数据的比较分析。 使用多种遗传学和药理学方法在个体基因水平上实现功能失活。 这种方法成功的关键是开发动态的、预测性的基因表达模型。 本提案的目的是开发计算和信息学工具来分析和解释与这些功能修饰相关的表达谱。 这些工具将对照经过验证的“黄金标准”数据集进行测试。 该模型系统将涉及分析SW1353软骨肉瘤细胞中的信号转导途径。 这一努力的组成部分是统计分析和实验设计之间的相互作用。 这种相互作用的努力是有可能的合作,内置到该项目。
英文摘要
Over the past few years powerful new methods have been devised that enable researchers to simultaneously study the dynamics of expression of an entire genome. This potentially vast quantity of data enables, in principle, the dissection of the complex genetic networks that control the patterns and rhythms of gene expression in the cell. The goal of the proposed work is to develop a systems analysis of whole genome expression profiles. Our aim is to infer regulatory networks from gene expression data and to validate these procedures with experimental results. To this end, the project will integrate a combination of efforts involving: systems modeling and visualization of large networks, experimentation on model systems, and development of database and bioinformatic tools. Our strategy for identifying genotypes associated with complex phenotype is to use a comparative analysis of time series data for normal and functional inactivated systems. The functional inactivation is achieved at the individual gene level using a variety of genetic and pharmacological methods. The key to the success of such an approach is the development of dynamic, predictive models of gene expression. The aim of this proposal is to develop the computational and informatic tools to analyze and interpret expression profiles associated with these functional modifications. These tools will be tested against a validated "gold-standard" data set. This model system will involve profiling signal transduction pathways in SW1353 chondrosarcoma cells. Integral to this effort is the interplay between statistical analysis and experimental design. Such interplay of efforts is made possible by the collaborations built into the project.
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Alignment algorithms applied to protein fold and remote homologue recognition
Alignment algorithms applied to protein fold and remote homologue recognition
Alignment algorithms applied to protein fold and remote homologue recognition
Time Series Analysis of Expression Profiles
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