Skip to main content
. 2018 Jul 25;13(7):e0200929. doi: 10.1371/journal.pone.0200929

Table 1. Nine categories and their descriptions.

Categories Description Systems-oriented or Biology-oriented
Metabolic Flux Analysis Measures the stoichiometric data of metabolites, and relies on modeling using non-differential equations and a few parameters. Systems-oriented
Development of high-throughput technologies These technologies include sequencing technologies, protein chips, DNA arrays, and mass spectrometry, etc. Biology-oriented
Algorithms, equations, and modeling This category includes development of algorithms, equations, modeling, and simulation techniques that relies heavily on mathematical knowledge. Systems-oriented
Omics research characterizing a real biological system Omics research relies on data produced by high-throughput technologies and modeling; the ultimate goal is offering a system-level characterization of a real biological system. Biology-oriented
Database development This category involves the launch of databases storing genes, pathways, proteins, etc. It also involves standardization of data and procedures, such as the Systems Biology Markup Language. Systems-oriented
Software development Software is developed to process, analyze, and visualize large data. Systems-oriented
Network properties These properties include robustness, dynamics, stochasticity, and emergent network properties that can be applied to every system, not just biological systems. The work is mostly mathematical and theoretical. Systems-oriented
The applications of systems biology
Systems biology is especially useful in tackling complex diseases like cancer, and has applications in bioengineering and synthetic biology. Biology-oriented
Biological Mechanisms This category involves using systems approach to understand a specific biological mechanism. Biology-oriented