Abstract
Complex systems theory is concerned with identifying and characterizing common design elements that are observed across diverse natural, technological and social complex systems. Systems biology, a more holistic approach to study molecules and cells in biology, has advanced rapidly in the past two decades. However, not much appreciation has been granted to the realization that the human cell is an exemplary complex system. Here, I outline general design principles identified in many complex systems, and then describe the human cell as a prototypical complex system. Considering concepts of complex systems theory in systems biology can illuminate our overall understanding of normal cell physiology and the alterations that lead to human disease.
Highlights
BD2K-LINCS Data Coordination and Integration Center; Mount Sinai Center for Bioinformatics; Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L
Different areas of scientific research such as computer science, sociology, mathematics, physics, economics and biology are increasingly realizing the importance of complex systems theory, because the same design patterns and concepts are emerging in these different fields of science
Complex environments may be just at an early stage within the complex system evolutionary process, on their way to gradually moving towards becoming a complex agent; once many complex agents of the same type exist in the environment, they can form a new layer of complexity which can serve as a foundation for the layer
Summary
Science and technology allow us to understand our environment as well as manipulate it and create new environments and new systems. Models that simulate real-world complex systems are built to capture the dynamics and architecture of a system to predict the system’s future behaviour and to explain its past behaviour Such models help us to better understand and potentially fix system failures, such as those happening in disease processes inside human cells. As more knowledge is accumulated about complex systems, such as the human cell, this knowledge can be fed back into the mathematical or computational models to refine them, making them more accurate This additional information adds more power and value to the models’ ability to capture the systems’ functionality in greater detail, and this enables making better predictions about how components and processes of the system come together to enable cellular behaviours such as responses to stimuli that induce cell proliferation, cell growth, cell differentiation/ 2 specialization or programmed cell death. We often find ourselves only using a small fraction of the measured data, only scratching the surface of a mine full of treasures
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