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Bioinformatics approaches to biomarker and drug discovery in aging and disease.

机译:在衰老和疾病中生物标志物和药物发现的生物信息学方法。

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摘要

Over the past two decades, high-throughput (HTP) technologies such as microarrays and mass spectrometry have fundamentally changed the landscape of aging and disease biology. They have revealed novel molecular markers of aging, disease state, and drug response. Some have been translated into the clinic as tools for early disease diagnosis, prognosis, and individualized treatment and response monitoring. Despite these successes, many challenges remain: HTP platforms are often noisy and suffer from false positives and false negatives; optimal analysis and successful validation require complex workflows; and the underlying biology of aging and disease is heterogeneous and complex. Methods from integrative computational biology can help diminish these challenges by creating new analytical methods and software tools that leverage the large and diverse quantity of publicly available HTP data.;In this thesis I report on four projects that develop and apply strategies from integrative computational biology to identify improved biomarkers and therapeutics for aging and disease. In Chapter 2, I proposed a new network analysis method to identify gene expression biomarkers of aging, and applied it to study the pathway-level effects of aging and infer the functions of poorly-characterized longevity genes. In Chapter 4, I adapted gene-level HTP chemogenomic data to study drug response at the systems level; I connected drugs to pathways, phenotypes and networks, and built the NetwoRx web portal to make these data publicly available. And in Chapters 3 and 5, I developed a novel meta-analysis pipeline to identify new drugs that mimic the beneficial gene expression changes seen with calorie restriction (Chapter 3), or that reverse the pathological gene changes associated with lung cancer (Chapter 5).;The projects described in this thesis will help provide a systems-level understanding of the causes and consequences of aging and disease, as well as new tools for diagnosis (biomarkers) and treatment (therapeutics).
机译:在过去的二十年中,诸如芯片和质谱之类的高通量(HTP)技术从根本上改变了衰老和疾病生物学的面貌。他们揭示了衰老,疾病状态和药物反应的新型分子标记。其中一些已作为早期疾病诊断,预后以及个性化治疗和反应监测的工具翻译成临床。尽管取得了这些成功,但仍然存在许多挑战:HTP平台通常嘈杂,并遭受误报和误报;最佳分析和成功验证需要复杂的工作流程;衰老和疾病的基本生物学是异质的和复杂的。集成计算生物学的方法可以通过创建新的分析方法和软件工具来减少这些挑战,这些方法和软件工具可以利用大量不同的公开HTP数据。确定用于衰老和疾病的改进的生物标志物和疗法。在第二章中,我提出了一种新的网络分析方法来识别衰老的基因表达生物标志物,并将其用于研究衰老的通路水平效应并推断出寿命较差的基因的功能。在第4章中,我调整了基因水平的HTP化学基因组数据,以研究系统水平的药物反应。我将药物与途径,表型和网络相关联,并建立了NetwoRx网站门户以使这些数据可公开获得。在第3章和第5章中,我开发了一种新颖的荟萃分析流程,以识别可模拟热量限制中有益基因表达变化的新药物(第3章),或逆转与肺癌相关的病理基因变化的新药物(第5章)。本文中描述的项目将有助于在系统级上了解衰老和疾病的原因和后果,以及新的诊断(生物标记物)和治疗(治疗方法)工具。

著录项

  • 作者

    Fortney, Kristen.;

  • 作者单位

    University of Toronto (Canada).;

  • 授予单位 University of Toronto (Canada).;
  • 学科 Bioinformatics.;Biophysics.;Pharmaceutical sciences.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 139 p.
  • 总页数 139
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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