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Systems Biology in the Context of Big Data and Networks

机译:大数据和网络环境下的系统生物学

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Science is going through two rapidly changing phenomena: one is the increasing capabilities of the computers and software tools from terabytes to petabytes and beyond, and the other is the advancement in high-throughput molecular biology producing piles of data related to genomes, transcriptomes, proteomes, metabolomes, interactomes, and so on. Biology has become a data intensive science and as a consequence biology and computer science have become complementary to each other bridged by other branches of science such as statistics, mathematics, physics, and chemistry. The combination of versatile knowledge has caused the advent of big-data biology, network biology, and other new branches of biology. Network biology for instance facilitates the system-level understanding of the cell or cellular components and subprocesses. It is often also referred to as systems biology. The purpose of this field is to understand organisms or cells as a whole at various levels of functions and mechanisms. Systems biology is now facing the challenges of analyzing big molecular biological data and huge biological networks. This review gives an overview of the progress in big-data biology, and data handling and also introduces some applications of networks and multivariate analysis in systems biology.
机译:科学正在经历两种迅速变化的现象:一种是计算机和软件工具的能力从TB增长到PB,甚至更高,其二是高通量分子生物学的进步,产生了与基因组,转录组,蛋白质组有关的数据,代谢组,相互作用组等。生物学已经成为数据密集型科学,因此,生物学和计算机科学已经在统计学,数学,物理学和化学等其他科学分支之间相互补充。多用途知识的结合已导致大数据生物学,网络生物学和生物学的其他新分支的出现。例如,网络生物学促进了对细胞或细胞成分和子过程的系统级理解。它通常也被称为系统生物学。该领域的目的是从功能和机制的各个层面理解生物或细胞。系统生物学现在面临着分析大分子生物学数据和巨大生物网络的挑战。这篇综述概述了大数据生物学和数据处理的进展,还介绍了网络和多元分析在系统生物学中的一些应用。

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