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Interactive visualization and model-based analysis of genomics data.

机译:交互式可视化和基于模型的基因组数据分析。

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摘要

Biotechnologies, such as DNA sequencing and microarray technology, have transformed research in molecular biology from being "gene-centric" to "genome-centric", opening new avenues in the areas of drug discovery, clinical diagnostics and agriculture. There is a pressing need for development of new computational and visualization techniques to gain biological knowledge from massive amounts of heterogeneous and complex genomics data. Computational methods transform biological questions into mathematical problems to produce large quantities of numerical results that require biological interpretation. Visual presentation of such data combined with interactive exploration will allow biologists to comprehend underlying biology. Motivated by these challenges of bridging the gaps between data processing by computational scientists and its interpretation by life scientists, this dissertation presents visualization tools for genomics data with easy-to-use interfaces.;Understanding the process of gene regulation is one of the most important and challenging questions for which the scientific community is increasingly looking for an answer in genomics data. Different types of genomics data shed light on different aspects of gene regulation making integration of data essential to get a handle on the whole process of gene regulation. To facilitate such integration, this dissertation presents a model of gene regulation that leads to a graph theoretic structure, which provides an invariant view of regulation from both the sequence and gene expression. Methods to obtain approximations to such a structure from gene expression data and DNA-protein interaction data are presented.
机译:DNA测序和微阵列技术等生物技术已将分子生物学研究从“以基因为中心”转变为“以基因组为中心”,为药物发现,临床诊断和农业领域开辟了新途径。迫切需要开发新的计算和可视化技术,以从大量的异构和复杂基因组学数据中获取生物学知识。计算方法将生物学问题转换为数学问题,以产生大量需要生物学解释的数值结果。这些数据的可视化展示与交互式探索相结合,将使生物学家能够理解基础生物学。受到弥合计算科学家之间的数据处理与生命科学家的解释之间的鸿沟的挑战的启发,本论文提出了具有易于使用的界面的基因组数据可视化工具。;了解基因调控的过程是最重要的过程之一和具有挑战性的问题,科学界正越来越多地在基因组学数据中寻找答案。不同类型的基因组学数据揭示了基因调控的不同方面,使得整合数据对于掌握基因调控的整个过程至关重要。为了促进这种整合,本文提出了一种基因调控模型,该模型导致了图论结构,从序列和基因表达两个角度提供了不变的调控观点。提出了从基因表达数据和DNA-蛋白质相互作用数据获得近似于这种结构的方法。

著录项

  • 作者

    Shah, Nameeta Yogeshkumar.;

  • 作者单位

    University of California, Davis.;

  • 授予单位 University of California, Davis.;
  • 学科 Computer Science.;Biology Bioinformatics.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 163 p.
  • 总页数 163
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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