With the deepening of people's understanding of objective things, they are no longer satisfied with the territory of simply solving problems, among which the complexity research in the field of life science has attracted the attention of many interdisciplinary scholars. The author summarizes the concept of complexity and the research on complexity and its extreme complexity in life science.
Keywords life science; Complexity science; Biological complexity
The concept of complexity science has been born for more than 20 years, during which a large number of scholars have made fruitful explorations from different fields. People hope to study the basic laws governing the operation of objective things more comprehensively and deeply from the perspective of the overall description of the whole and part of the objective world and the hierarchical relationship in the evolution of time and space, and establish the theoretical basis for the development of science and technology in the new century to guide the new development practice.
Among them, the complexity research in the field of life science has attracted the attention of many interdisciplinary scholars, and some people call it biological complexity research. Biological complexity science mainly explores the intersection of some traditional disciplines. To be precise, it is to seek a quantitative and comprehensive method to deeply understand the complex interactions among various life systems, including biological, behavioral, chemical and physical interactions, as well as the comprehensive interactions among ecology, environment and society [1].
1 Concept and category of complexity science research
The definition of complexity is relative to simplicity, which has always been a guiding principle of modern natural science, especially physics. Many scientists think that the basic laws of nature are simple. The basic idea of reductionism is to find out the simple mechanism behind complex phenomena or things. In fact, there are simple laws or processes behind some complex things or phenomena.
There is no unified concept of complexity, but there are different formulations according to different research objects. For example, from the perspective of entropy, complexity is equal to the disorder determined by entropy and thermodynamics of a system; Information angle: Complexity equals the system's ability to surprise observers; Fractal size: the "fuzzy state" of the system, that is, the degree of detail displayed on smaller and smaller sizes; Effective complexity: the degree to which a system shows "regularity" rather than randomness; System complexity: the diversity shown by different levels of an architecture system; Complexity of grammar: the universality of the language needed to describe a system; Thermodynamic depth: the amount of thermodynamic resources needed to organize a system from scratch; Complexity of time calculation: the time required for a computer to describe a system or solve a problem; Complexity of spatial computing: the storage space required for a computer to describe a system or solve a problem [2]; Wait a minute.
Since the rise of system science in the 1930s, people have gradually realized that a system is greater than the sum of its components, has a hierarchical structure and a functional structure, constantly develops and changes, and often exchanges materials, energy and information with its environment (outside), even when it is far from equilibrium, it can remain stable (self-organized). Deterministic system has its inherent randomness (chaos), while stochastic system has its inherent certainty (sudden appearance).
Complexity science often studies complex systems, mainly in the following forms: (1) The units of the system are widely and closely linked to form a network. Therefore, the change of each unit will be influenced by the change of other units and will cause the change of other units. (2) The system has a multi-level and multi-functional structure, and each level becomes a unit to build its upper layer, which is also conducive to the realization of a certain function of the system. (3) In the process of development, the system can continue to learn and reorganize, and improve its hierarchical structure and functional structure. (4) The system is open, closely related to the environment, can interact with the environment, and can continuously develop and change in the direction of better adapting to the environment. (5) The system is dynamic, it is constantly in the process of development and change, and the system has certain ability to predict future development and change.
Generally speaking, the basic method of complexity research is the combination of (1) qualitative judgment and quantitative calculation. (2) The combination of micro-analysis and macro-synthesis. (3) The combination of reductionism and holism. (4) The combination of scientific reasoning and philosophical speculation.
Theoretical tools used in complex scientific research: (1) nonlinear science-nonlinear dynamic system theory (stability and bifurcation theory, chaos, soliton) and statistical mechanics (fractal, scale), research on complex random phenomena in unbalanced systems; (2) Computer simulation-it is a very important means and has been widely used in the research of complex science; (3) Computational intelligence; (4) Mathematical logic; (5) Decision-making technology under uncertain conditions; (6) Comprehensive integration technology; (7) Overall optimization technology, etc.
2 Life Science and Complexity Research
The research objects of life science are all complex systems (with the characteristics of relevance, diversity, self-study, self-organization, openness and dynamics). Because of its complexity, the research system of life science lacked understanding of its composition and evolution before, which attracted the attention of complexity science researchers. In recent decades, people have discussed the typical characteristics of biological systems, such as integrity, correlation, network hierarchy, statistical fluctuation, internal and external randomness, fuzziness, openness and historicity. The characteristics of organisms themselves and the evolution of organisms make people's way of thinking change from the study of simple systems in physics to the study of complex systems in biology [3].
Gene is the basic code of life inheritance. The complex structure and function of organisms are not only determined by genes, but also by a large number of non-coding information and non-coding genes in the genome. Therefore, the complex structure and function of an organism are not only determined by genes, nor by a large number of non-coding information in the genome, but by the complex and dynamic interaction of these elements at all levels of the organism.
As the command and coordination center of life system-nervous system, its central functional structure is brain, and the scientific research of brain function has been a hot spot in complex scientific fields in recent ten years. The brain has a complex structure, and its organizational levels are as follows: molecules, membranes, synapses, neurons, nuclei, circuits, networks, layers, projections and systems. Some advanced functions of the brain cannot be observed at a lower level, and some are collective behaviors produced by the interaction between various units. The law of human thinking is constantly changing, but the law at the bottom is unchanged. The complexity of brain function is first reflected in the high nonlinearity, instability and adaptability of each nervous subsystem; Secondly, it is reflected in the non-uniformity and large-scale parallelism of their interconnection. Moreover, even very simple nervous systems have amazing complexity, which is reflected in their functions, evolutionary history, structure and coding methods. For example, the time series of single neuron discharge contains complex and diverse time patterns, which reflects the complex dynamic process in nerve cells [4]. EEG is a spontaneous bioelectric activity of the central nervous system, which contains rich information about the state and changes of the nervous system, so it is widely used in clinical and neurophysiological research. Nowadays, people have established a dynamic model of EEG to study the chaotic phenomenon, which shows the significance of dynamic model method for studying the normal physiological and pathological state of the brain [5].
In recent years, the brain control system has been realized and developed in the control field, that is, the man-machine fusion control system based on EEG signals, which is directly based on EEG signals and controlled through brain-computer interface. The research of "brain control" involves neuroscience, computer science, control science and psychology. Related research has developed a "brain control technology" that uses the brain's thinking to control the motion state of various facilities through electronic interfaces and achieve the expected results. This technology has important application value in many aspects such as medical treatment.
Artificial life is a new direction developed in recent 10 years, and it is a complex research characterized by evolution. Artificial life is devoted to studying the universal characteristics of life forms (not limited to specific carriers). Life on earth is regarded as a specific life form with a specific carrier-protein, and the evolution of life on earth only represents a specific evolutionary path. Therefore, other substances can be used to construct life forms instead of carriers, endow them with life characteristics, make them have life phenomena such as evolution, heredity and variation, and obtain the universal behavior of life [2].
Others, such as heart rate variability and lumen strain of cardiovascular system; Prevention, treatment and mathematical modeling of dynamic diseases (diseases characterized by abnormal time structure, such as periodic fever and periodic joint swelling); Population reproduction of ecosystem; The law of disease transmission in epidemic diseases; Dynamic process of biochemical reaction; The dynamic process of signal generation, transmission and transduction in immune system reflects the complexity of biological system and belongs to the category of complexity science research.
Because the diversity and complexity of life determine the complexity of clinical medicine itself; Disease is complex, not only the pathological process of life itself is complex, but also psychological, social and environmental factors will affect the pathological process; Many complicated diseases, such as cardiovascular diseases, cancer, AIDS, etc. , is the result of multi-level and multi-level life factors. Modern medicine is a one-sided and fragmented understanding of life and disease under the guidance of reductionism, which still stays at the level of analysis and description; Therefore, it is necessary to resort to complexity research methods. Breakthroughs have been made in research methods and concepts.
The unique thinking method of traditional Chinese medicine in the motherland, grasping the overall state of complex systems, has similar ideas to complexity research. Traditional Chinese medicine has put forward many propositions about the interaction between human body and the interaction between human body and environment, which has prepared rich materials for modern medical research. To understand the theoretical system of traditional Chinese medicine, we must also use the latest knowledge of physics, biology, mathematics, cybernetics, system theory and other disciplines.
For us, complexity science is a field full of unknowns. The research methods include reductionism, synthesis and system theory. These two ideas are experiencing collision and beginning to merge. But as far as the research object is concerned, the problems it studies are not just emerging, but because of the depth of people's understanding and its own difficulty, such problems have been shelved. At present, the study of complexity has made initial progress in some disciplines. With the progress of science and technology and the deepening of human understanding of nature and itself, the complexity problem in life science will inevitably be gradually recognized and solved.