From ~omics to integrative networks

Systems biology can be explained from a reductionistic view: the systems in question are just collections of interacting components of a well defined single type (e.g. systems of interacting proteins). Unlike molecular biology, which focuses on molecules, such as the sequence of nucleotide acids and proteins, systems biology focuses on systems that are composed of molecular components. Therefore, systems biology can be seen as high-throughput reductionism by exhaustive, simultaneous descriptions of a biological system. Systems cell biology can be described as the attempt to achieve a mechanistic understanding of the functional components of cells and of entire organisms including their development by predicting their properties from numerical data that arise from interaction analyses of many system elements. In conclusion, systems biology represents the integration of measurements of genomics, transcriptomics, proteomics and metabolomics. 

Systems biology can also be explained from an integrative view: multiscale, multilevel explanations of organismal properties (e.g. metabolism, genetic network, signalling network). The goal of systems biology is being able to model a living organism. To reach this goal it examines the structure and dynamics of cellular and organismal function, rather than the characteristics of isolated parts of a cell or organism. For this, systems biology is bringing mathematical and computational methods to bear on genetics, physiology, development and evolution, so as to deal with multiscale complexities without losing sight of them. 

Understanding complex biological systems

Understanding complex biological systems requires the integration of experimental and computational research

• “Systems Biology is a knowledge-based approach combining acquisition, integration and management of experimental data with computer modelling and simulation to understand, predict, and ultimately control functionalities of complex biological systems."
• “Systems biology studies biological systems by systematically perturbing them (biologically, genetically, or chemically); monitoring the gene, protein, and informational pathway responses; integrating these data; and ultimately, formulating mathematical models that describe the structure of the system and its response to individual perturbations.”
• “Theoretical systems biology aims at understanding the functioning of cells by means of models that operate on the cell scale.”

A systems level understanding of a biological system

A systems level understanding of a biological system can be derived from insight into four key properties:

1. understanding of system structures, such as gene regulatory and biochemical networks, as well as physical structures
2. understanding of system dynamics, to predict how a biological system will behave over time under various conditions, using both quantitative and qualitative analysis as well as construction of theories/models with powerful prediction capability
3. understanding of system control methods, which are mechanisms that systematically control the state of the cell, resulting in its robustness and stability.
4. understanding of system design methods, to develop strategies to modify and construct biological systems having the desired properties based on definite design principles and simulations instead of blind trial-and-error.