Systems biology in the context of "In silico"

Earth system science (ESS) is the application of systems science to the Earth. In particular, it considers interactions and 'feedbacks', through material and energy fluxes, between the Earth's sub-systems' cycles, processes and "spheres"—atmosphere, hydrosphere, cryosphere, geosphere, pedosphere, lithosphere, biosphere, and even the magnetosphere—as well as the impact of human societies on these components. At its broadest scale, Earth system science brings together researchers across both the natural and social sciences, from fields including ecology, economics, geography, geology, glaciology, meteorology, oceanography, climatology, paleontology, sociology, and space science. Like the broader subject of systems science, Earth system science assumes a holistic view of the dynamic interaction between the Earth's spheres and their many constituent subsystems fluxes and processes, the resulting spatial organization and time evolution of these systems, and their variability, stability and instability. Subsets of Earth System science include systems geology and systems ecology, and many aspects of Earth System science are fundamental to the subjects of physical geography and climate science.

Biocybernetics is the application of cybernetics to biological science disciplines such as neurology and multicellular systems. Biocybernetics plays a major role in systems biology, seeking to integrate different levels of information to understand how biological systems function. The field of cybernetics itself has origins in biological disciplines such as neurophysiology. Biocybernetics is an abstract science and is a fundamental part of theoretical biology, based upon the principles of systemics. Biocybernetics is a psychological study that aims to understand how the human body functions as a biological system and performs complex mental functions like thought processing, motion, and maintaining homeostasis. Within this field, many distinct qualities allow for different distinctions within the cybernetic groups such as humans and insects such as beehives and ants.

Humans work together but they also have individual thoughts that allow them to act on their own, while worker bees follow the commands of the queen bee. Although humans often work together, they can also separate from the group and think for themselves. A unique example of this within the human sector of biocybernetics would be in society during the colonization period, when Great Britain established their colonies in North America and Australia. Many of the traits and qualities of the mother country were inherited by the colonies, as well as niche qualities that were unique to them based on their areas like language and personality—similar vines and grasses, where the parent plant produces offshoots, spreading from the core. Once the shoots grow their roots and get separated from the mother plant, they will survive independently and be considered their plant. Society is more closely related to plants than to animals since, like plants, there is no distinct separation between parent and offspring. The branching of society is more similar to plant reproduction than to animal reproduction. Humans are a K-selected species that typically have fewer offspring that they nurture for longer periods than r-selected species. It could be argued that when Britain created colonies in regions like North America and Australia, these colonies, once they became independent, should be seen as offspring of British society. Like all children, the colonies inherited many characteristics, such as language, customs and technologies, from their parents, but still developed their own personality. This form of reproduction is most similar to the type of vegetative reproduction used by many plants, such as vines and grasses, where the parent plant produces offshoots, spreading ever further from the core. When such a shoot, once it has produced its own roots, gets separated from the mother plant, it will survive independently and define a new plant. Thus, the growth of society is more like that of plants than like that of the higher animals that we are most familiar with, there is not a clear distinction between a parent and its offspring.

Supramolecular chemistry is the branch of chemistry concerning chemical systems composed of discrete numbers of molecules. The strength of the forces responsible for spatial organization of the system ranges from weak intermolecular forces, electrostatic charge, or hydrogen bonding to strong covalent bonding, provided that the electronic coupling strength remains small relative to the energy parameters of the component. While traditional chemistry concentrates on the covalent bond, supramolecular chemistry examines the weaker and reversible non-covalent interactions between molecules. These forces include hydrogen bonding, metal coordination, hydrophobic forces, van der Waals forces, pi–pi interactions and electrostatic effects.

Important concepts advanced by supramolecular chemistry include molecular self-assembly, molecular folding, molecular recognition, host–guest chemistry, mechanically-interlocked molecular architectures, and dynamic covalent chemistry. The study of non-covalent interactions is crucial to understanding many biological processes that rely on these forces for structure and function. Biological systems are often the inspiration for supramolecular research.

Conrad Hal Waddington CBE FRS FRSE (8 November 1905 – 26 September 1975) was a British developmental biologist, paleontologist, geneticist, embryologist and philosopher who laid the foundations for systems biology, epigenetics, and evolutionary developmental biology.

His theory of genetic assimilation probably has a Darwinian explanation, which contrast with the fact that Waddington himself was very critic about the notion of natural selection and Neo-Darwinism. Leading evolutionary biologists including Theodosius Dobzhansky and Ernst Mayr considered that Waddington was using genetic assimilation to support so-called Lamarckian inheritance, the acquisition of inherited characteristics through the effects of the environment during an organism's lifetime.

Modelling biological systems is a significant task of systems biology and mathematical biology. Computational systems biology aims to develop and use efficient algorithms, data structures, visualization and communication tools with the goal of computer modelling of biological systems. It involves the use of computer simulations of biological systems, including cellular subsystems (such as the networks of metabolites and enzymes which comprise metabolism, signal transduction pathways and gene regulatory networks), to both analyze and visualize the complex connections of these cellular processes.

An unexpected emergent property of a complex system may be a result of the interplay of the cause-and-effect among simpler, integrated parts (see biological organisation). Biological systems manifest many important examples of emergent properties in the complex interplay of components. Traditional study of biological systems requires reductive methods in which quantities of data are gathered by category, such as concentration over time in response to a certain stimulus. Computers are critical to analysis and modelling of these data. The goal is to create accurate real-time models of a system's response to environmental and internal stimuli, such as a model of a cancer cell in order to find weaknesses in its signalling pathways, or modelling of ion channel mutations to see effects on cardiomyocytes and in turn, the function of a beating heart.