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KAIST부설 한국과학영재학교 온라인 과학매거진 코스모스

  • 블랙 페이스 북 아이콘
  • 블랙 인스 타 그램 아이콘

Systems Biology

최종 수정일: 2020년 11월 9일

What is Systems Biology?

A system-level analysis and control of complex biological networks by combining mathematical modeling, computer simulation, and biological experiments to unravel the hidden logic of life and to eventually control the biological phenomena as we want.

Where can it be used?

Reverse control of cancer and aging

Cancer and aging are generally regarded as irreversible biological phenomena. Might it be possible to reverse these processes? Historically, there have been some reports about such reversion under particular circumstances, indicating the possibility of it, but no systematic analysis or experiment has been attempted so far. A team at KAIST is currently conducting creative research on reverse control of cancer and aging through a systems biological approach. Through an extensive large-scale computer simulation analysis of these models, the team is trying to identify molecular targets that can reverse cancer and aging processes and to further test the resulting changes in dynamic features when those targets are controlled. We also carry out experimental validation of the results through both cell and organoid experiments.

Computer simulation analysis for personalized therapy of cancer

A model of personalized cancer therapy

Systems biology suggests a new paradigm for precision medicine. Teams are developing computer simulation models for primary molecular regulatory networks of cancer on the basis of biological big data. By mapping each individual patient’s genetic variation to the simulation model, scientists can use the model to find an optimized personalized therapy. Individually optimized therapeutic strategies are investigated by analyzing the dynamical features of our personalized computer simulation model through supercomputing-based large-scale simulation analysis.

Brain network control

Our brain comprises complex networks of neurons through synaptic interactions, and brain functions are induced by the dynamics of such complex networks. For instance, the selective synchronization is a basis for normal brain functioning, so synchronization disruption can cause functional abnormalities that leads to diverse brain disorders. Teams are investigating the physical and functional regulations in brain and principles of those regulations using large-scale computational models of neuronal networks on the basis of multi-modal brain connectome data. The ultimate goal is to investigate the emergent properties of complex neuronal networks in connection with brain functions and disorders, and to unravel/control the underlying hidden working principles. For this purpose, teams are constructing real human brain network models based on the human connectome data and developing brain network control strategies to overcome various brain disorders.

Analysis and control of biological networks

A mathematical representation of a metabolic network model with nodes accounting for genes, metabolites, and reactions.

All living-systems are composed of complex networks of their functional subunits, and their biological phenomena are determined by dynamic changes of those networks. Therefore, it is crucial to control those complex networks to regulate the biological phenomena in the way we want. Systems biology explores the functions of such biological networks by analyzing both topological as well as dynamical properties. The aim is to investigate the relationship between topological properties and biological functions, and to eventually develop practically useful control strategies with which we can regulate the network dynamics.

Bio-inspired Engineering Based on Systems Biology

Teams of KAIST are developing a new realm of engineering named bio-inspired engineering based on systems biology, which applies our system-level understanding on biological mechanisms to engineering to find out a novel solution to unsolved engineering problems. For example, they develop self-repairing electrical circuits inspired from biological networks.

Iron Man’s self-regenerating ‘Bleeding Edge’ suit, as seen in <Avengers: Infinity War>, may be possible to recreate in real life.


Prof. Kwang-Hyun Cho’s Laboratory for Systems Biology and Bio-Inspired Engineering


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