Complexity and Emergent Proterties in Biology
Emergent properties are characteristics or behaviors that arise from the interactions of components within a system, but are not evident in the individual components themselves. These properties are surprises
that emerge when parts come together to form a larger whole. For example, the property of life
is an emergent property that arises from the complex interactions of cells within a multicellular organism, but is not a property of individual cells alone.
(From Encyclopaedia Britannica)
Many of the most-critical aspects of how a cell works result from the collective behaviour of many molecular parts, all acting together. Those collective properties—often called emergent properties—are critical attributes of biological systems, as understanding the individual parts alone is insufficient to understand or predict system behaviour. Thus, emergent properties necessarily come from the interactions of the parts of the larger system. As an example, a memory that is stored in the human brain is an emergent property because it cannot be understood as a property of a single neuron or even many neurons considered one at a time. Rather, it is a collective property of a large number of neurons acting together.
Information
One of the most-important aspects of the individual molecular parts and the complex things they constitute is the information that the parts contain and transmit. In biology information in molecular structures—the chemical properties of molecules that enable them to recognize and bind to one another—is central to the function of all processes. Such information provides a framework for understanding biological systems, the significance of which was captured insightfully by American theoretical physical chemist Linus Pauling and French biologist Emil Zuckerkandl, who stated in a joint paper, Life is a relationship among molecules and not a property of any one molecule.
In other words, life is defined in terms of interactions, relationships, and collective properties of many molecular systems and their parts.
The central argument concerning information in biology can be seen by considering the heredity of information, or the passing on of information from one generation to the next. For a given species, the information in its genome must persist through reproduction in order to guarantee the species' survival. DNA is passed on faithfully, enabling a species' genetic information to endure and, over time, to be acted on by evolutionary forces. The information that exists in living things today has accumulated and has been shaped over the course of more than 3.4 billion years. As a result, focusing on the molecular information in biological systems provides a useful vantage point for understanding how living systems work.
That the emergent properties derived from the collective function of many parts are the key properties of biological systems has been known since at least the first half of the 20th century. They have been considered extensively in cell biology, physiology, developmental biology, and ecology. In ecology, for example, debate regarding the importance of complexity in ecological systems and the relationship between complexity and ecological stability began in the 1950s. Since then, scientists have realized that complexity is a general property of biology, and technologies and methods to understand parts and their interactive behaviours at the molecular level have been developed. Quantitative change in biology, based on biological data and experimental methods, has precipitated profound qualitative change in how biological systems are viewed, analyzed, and understood. The repercussions of that change have been immense, resulting in shifts in how research is carried out and in how biology is understood.
Engineers and mathematicians have provided valuable insights into the nature of information, particularly related to communications, and biologists have adapted some of those insights to the study of biological systems. A significant area of research in biology centres on the question of whether higher-order biological processes can be represented from an information perspective. The conceptual tools for looking at biological phenomena are based on mathematical ideas about information and computing, but significant further development is required before a satisfactory theoretical basis is realized. For example, a key aspect of describing and measuring biological information is the context in which the information operates, which has been difficult to represent in a clear and useful way. An example of the type of challenge that researchers face is the process of gene expression, which involves the production of a specific protein molecule from genetic information. A number of factors impinge on the expression of any one gene—from the type of cell involved to the external signals received by and the metabolic state of the cell to preexisting states of gene expression. Efforts to understand those factors form a major area of research in modern biology.
Although some small networks, such as certain metabolic networks in bacteria or yeast, are relatively well characterized, more-complex networks, such as developmental networks, remain only partially understood. Mathematical concepts relevant to the study of both types of networks have been developed and implemented. Still, few biological systems have been characterized sufficiently to enable researchers to model them as networks. Examples include the lactose- and galactose-utilization systems in certain bacteria, such as Escherichia coli and Streptococcus. However, wider interactions of those networks are comparatively less well understood. The early embryonic development of the sea urchin is another system that has been effectively modeled. Models offer unique insight into biological development and physiology, and scientists have envisioned a future when models will become available for most biological systems. Indeed, quantitative models could ultimately come to embody hypotheses about the structure and function of any biological system in question.