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项目总结/摘要 动物生物学中最大的挑战之一是了解基因组序列信息如何被转录因子读取,以在发育胚胎的调控网络中产生基因表达模式。该项目是一个更广泛的计划项目的一部分,该计划项目将整合计算建模和湿实验室方法,以应对这一挑战,相信只有定量,预测 已经实验验证的数学模型可以提供对动物转录网络建模所需的严格理解。 该项目对整个计划的贡献将是开发预测计算模型,以了解负责将转录因子靶向体内DNA的分子机制。在初步研究中,我们已经表明,我们可以预测在体内DNA结合与合理的成功使用作为输入,只有在体外DNA结合特异性和在体内染色质可及性信息和一个简单的, 广义隐马尔可夫模型(gHMM)。然而,这些模型不够准确。因此,我们将开发更复杂的马尔可夫随机场模型,同时考虑所有的32个主要调控转录因子在果蝇胚盘网络,一些普遍表达的转录因子,核小体,以及所有这些蛋白质与DNA和彼此的相互作用。 我们将建模分为两个目标。第一个将扩展我们目前的染色质可及性模型,以确定是什么驱动核小体在胚胎中的基因组分布,以及核小体结构是否以及如何在胚胎中进行空间调控。第二个目的是确定和评估靶向转录因子的DNA在体内的分子力量。我们的模型将在与项目1和2以及表达和数据库核心合作进行的一系列转基因实验中进行测试,改进和验证。我们期望我们的模型将揭示适用于所有动物系统的体内靶向转录因子到DNA的一般原则。 通过帮助建立如何读取动物基因组中的转录信息,该项目将有助于开发人类遗传疾病的治疗方法和了解动物发育。
英文摘要
Project Summary/Abstract One of the greatest challenges in animal biology is to learn how genomic sequence information is read by transcription factors to produce patterns of gene expression within the context of regulatory networks in developing embryos. This Project is part of a broader Program Project that will integrate computational modeling and wet laboratory methods to address this challenge in the belief that only quantitative, predictive mathematical models that have been validated experimentally can provide the rigorous understanding required for modeling transcriptional networks of animals. This Project's contribution to the overall Program will be to develop predictive computational models to understand the molecular mechanisms responsible for targeting transcription factors to DNA in vivo. In Preliminary Studies, we have shown that we can predict in vivo DNA binding with reasonable success using as input only in vitro DNA binding specificity and in vivo chromatin accessibility information and a simple generalized Hidden Markov Model (gHMM). The models are not sufficiently accurate, however. Therefore, we will develop more sophisticated Markov Random Field models that simultaneously consider all of the 32 principal regulatory transcription factors in the Drosophila blastoderm network, a number of ubiquitously expressed transcription factors, nucleosomes, and all of these proteins interactions with DNA and each other. We have divided our modeling into two Aims. The first will extend our current models for chromatin accessibility to determine what drives the genomic distribution of nucleosomes in the embryo, and whether and how nucleosome structure is spatially regulated across the embryo. The second seeks to identify and evaluate the molecular forces that target transcription factors to DNA in vivo. Our models will be tested, refined and validated in a series of transgenic experiments conducted in collaboration with Projects 1 and 2 and the Expression and Database Core. We expect that our models will uncover general principles governing the targeting transcription factors to DNA in vivo that will be applicable to all animal systems. By helping to establishing how to read transcriptional information in animal genomes, this Project will aid both the development of therapeutics for human genetic diseases and the understanding of animal development.
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Removing statistical bottle-necks in data analysis for the ENCODE Consortium
Removing statistical bottle-necks in data analysis for the ENCODE Consortium
Removing statistical bottle-necks in data analysis for the ENCODE Consortium
Removing statistical bottle-necks in data analysis for the ENCODE Consortium
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