Summary
An integrative approach modelling interactions among genes, proteins and metabolites as networks.
In depth
Combines experiments and computation to study networks of interactions. Tools: omics data, network analysis, ODE models and Boolean models. Emphasises emergent properties such as oscillations and robustness.
Integrates measurement, modelling and perturbation. Network motifs such as feedback and feed-forward loops give dynamic behaviours. Whole-cell models simulate all processes in a minimal bacterium.
Key idea: understanding parts is not enough, one must study their interactions.
Systems biology studies biological systems as interacting networks rather than isolated parts, combining large-scale data with mathematical models. Emergent behaviours such as oscillations, bistable switches, robustness and feedback arise from network structure.
Approaches are top-down (omics data to infer networks) and bottom-up (detailed models from known mechanisms). Examples include models of the cell cycle, circadian clocks, metabolic flux balance analysis and whole-cell simulations of Mycoplasma.
Example: modelling signalling in cancer cells can predict drug combinations.
Key idea: the whole is more than the sum of the parts, and iterating between experiment and model reveals unexpected behaviour.
Frequently asked questions
What is Systems Biology?
An integrative approach modelling interactions among genes, proteins and metabolites as networks.
Which area of biology covers Systems Biology, and how advanced is it?
Systems Biology is one of the 56 topics in Biotechnology & Genomics. It is rated Advanced, so it suits learners who want specialist depth. Related topics in this area include Machine Learning in Biology, Synthetic Biology, Proteomics.
Can you give an example of Systems Biology?
Modelling the cell cycle as a bistable switch.
What should I learn before Systems Biology?
Work through the Beginner topics in Biotechnology & Genomics first, such as Biotechnology, Genetic Engineering, Selective Breeding, then return to Systems Biology. Advanced topics assume the Intermediate vocabulary.
What topics are related to Systems Biology?
The closest topics to Systems Biology are Machine Learning in Biology, Synthetic Biology, Proteomics, Bioinformatics. Comparing them side by side is a good way to see how the ideas connect.
How can I check that I understand Systems Biology?
Read the summary and the in-depth section, then use the quick check on the interactive lesson for Systems Biology. To practise the whole of Biotechnology & Genomics, use the Biotechnology & Genomics quiz.
How is Systems Biology different from Machine Learning in Biology?
Systems Biology: An integrative approach modelling interactions among genes, proteins and metabolites as networks. Machine Learning in Biology: Algorithms learn patterns in sequence, image and clinical data to predict function and disease. Read both side by side and note what each one explains.
How should I study Systems Biology step by step?
First, read the summary and write the definition in your own words. Second, read the in-depth section and note any example. Third, compare it with Machine Learning in Biology and explain the difference aloud. Finally, take the Biotechnology & Genomics quiz and come back to this page for any question you miss.