Review
Plant systems biology comes of age

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‘Omics’ research approaches have produced copious data for living systems, which have necessitated the development of systems biology to integrate multidimensional biological information into networks and models. Applications of systems biology to plant science have been rapid, and have increased our knowledge about circadian rhythms, multigenic traits, stress responses and plant defenses, and have advanced the virtual plant project.

Section snippets

Biological systems and systems biology in plants

The practice of integrating physiological, morphological, molecular, biochemical and genetic information has long been applied to biological research, and in diverse fields such as plant breeding and ecology [1]. The development of modern systems biology was driven by the need to assimilate the large amounts of data generated by genome-scale studies into biologically meaningful interpretations. Nevertheless, the definition of systems biology is still contentious; some researchers emphasize the

Advances in plant systems biology – a network perspective

Network (see Glossary) construction and analysis is one of the most common approaches to describe biological systems. Networks can be either static or dynamic, and their components can include genes, proteins, cis-elements, metabolites and other molecules. Here, we focus on four network types, including gene-to-metabolite networks, protein–protein interaction networks, transcriptional regulatory networks and gene regulatory networks (Figure 1). The first three types of networks are often

Advances in plant systems biology – a biological perspective

There are several practical problems plaguing agriculture that are being addressed using systems biology. Examples of areas in plant science that have been addressed using systems biology are quantitative traits and plant stress and defense.

The promises and challenges of plant systems biology

There are three domains that must be addressed to take full advantage of plant systems biology: (i) omics technology development; (ii) data integration into usable formats and (iii) data analysis within the domain of bioinformatics. Among these, bioinformatics probably needs the most attention because it is essential that biological data be normalized, standardized and visualized to build integrated models 78, 79, 80 (Figure 2). The limitation of systems biology is greatly tied to data

Glossary

Data mining
the computational process to search for consistent patterns or systemic relationships among the variables in a complex dataset. It includes several popular techniques, such as neural network, decision tree and logistic regression.
Data modeling
the computational approach to determine relationships among concepts or objects. In systems biology, data modeling is used to elucidate relationships among system elements based on the biological information.
Data visualization
techniques to

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      Systems biology is the collective study of various components of a biological entity as a self-contained system. For example, genes, transcripts, proteins, metabolites and environmental factors can be modeled as a multi-scale system to understand how changing one stress signal would influence various other parameters (Cui et al., 2008; Yuan et al., 2008; Fukushima et al., 2009, 2014; McClung and Gutierrez, 2010; Schneider and Collmer, 2010; Elena et al., 2011; Muers, 2011; Gutierrez, 2012; Weston et al., 2012; Zurbriggen et al., 2012; Lee, 2014; Sheth and Thaker, 2014; Petersson et al., 2015; Schmid et al., 2015; Yang and Wei, 2015; Kumar et al., 2016; Peyraud et al., 2017). As plant biology experiments are time-consuming and often expensive and labor intensive, bioinformatics approaches offer an affordable, complementary approach to help the plant biologists.

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