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用于理解真菌致病性的信号通路的生化系统分析。

Biochemical systems analysis of signaling pathways to understand fungal pathogenicity.

作者信息

Garcia Jacqueline, Sims Kellie J, Schwacke John H, Del Poeta Maurizio

机构信息

Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, South Carolina, USA.

Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, South Carolina, USA.

出版信息

Methods Mol Biol. 2011;734:173-200. doi: 10.1007/978-1-61779-086-7_9.

Abstract

Over the past decade, researchers have recognized the need to study biological systems as integrated systems. While the reductionist approaches of the past century have made remarkable advances of our understanding of life, the next phase of understanding comes from systems-level investigations. Additionally, biology has become a data-intensive field of research. The introduction of high throughput sequencing, microarrays, high throughput proteomics, metabolomics, and now lipidomics are producing significantly more data than can be interpreted using existing methods. The field of systems biology brings together methods from computer science, modeling, statistics, engineering, and biology to explore the volumes of data now being produced and to develop mathematical representations of metabolic, signaling, and gene regulatory systems. Advances in these methods are allowing biologists to develop new insights into the complexities of life, to predict cellular responses and treatment outcomes, and to effectively plan experiments that extend our understanding. In this chapter, we are providing the basic steps of developing and analyzing a small S-system model of a biochemical pathway related to sphingolipid metabolism in the regulation of virulence of the human fungal microbial pathogen Cryptococcus neoformans (Cn).

摘要

在过去十年中,研究人员已经认识到将生物系统作为一个整体系统进行研究的必要性。虽然上个世纪的还原论方法在我们对生命的理解上取得了显著进展,但下一阶段的理解将来自系统层面的研究。此外,生物学已成为一个数据密集型的研究领域。高通量测序、微阵列、高通量蛋白质组学、代谢组学以及现在的脂质组学的引入,所产生的数据量远远超过了使用现有方法所能解读的范围。系统生物学领域将计算机科学、建模、统计学、工程学和生物学的方法结合起来,以探索目前正在产生的大量数据,并开发代谢、信号传导和基因调控系统的数学表示。这些方法的进步使生物学家能够对生命的复杂性有新的认识,预测细胞反应和治疗结果,并有效地规划扩展我们理解的实验。在本章中,我们将介绍开发和分析一个与新型隐球菌(Cn)毒力调节中鞘脂代谢相关的生化途径的小型S系统模型的基本步骤。

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