Related Research Articles
Bioinformatics is an interdisciplinary field of science that develops methods and software tools for understanding biological data, especially when the data sets are large and complex. Bioinformatics uses biology, chemistry, physics, computer science, data science, computer programming, information engineering, mathematics and statistics to analyze and interpret biological data. The process of analyzing and interpreting data can sometimes be referred to as computational biology, however this distinction between the two terms is often disputed. To some, the term computational biology refers to building and using models of biological systems.
In philosophy, systems theory, science, and art, emergence occurs when a complex entity has properties or behaviors that its parts do not have on their own, and emerge only when they interact in a wider whole.
Computational biology refers to the use of techniques in computer science, data analysis, mathematical modeling and computational simulations to understand biological systems and relationships. An intersection of computer science, biology, and data science, the field also has foundations in applied mathematics, molecular biology, cell biology, chemistry, and genetics.
Computational neuroscience is a branch of neuroscience which employs mathematics, computer science, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system.
Computer simulation is the running of a mathematical model on a computer, the model being designed to represent the behaviour of, or the outcome of, a real-world or physical system. The reliability of some mathematical models can be determined by comparing their results to the real-world outcomes they aim to predict. Computer simulations have become a useful tool for the mathematical modeling of many natural systems in physics, astrophysics, climatology, chemistry, biology and manufacturing, as well as human systems in economics, psychology, social science, health care and engineering. Simulation of a system is represented as the running of the system's model. It can be used to explore and gain new insights into new technology and to estimate the performance of systems too complex for analytical solutions.
The map–territory relation is the relationship between an object and a representation of that object, as in the relation between a geographical territory and a map of it. Mistaking the map for the territory is a logical fallacy that occurs when someone confuses the semantics of a term with what it represents. Polish-American scientist and philosopher Alfred Korzybski remarked that "the map is not the territory" and that "the word is not the thing", encapsulating his view that an abstraction derived from something, or a reaction to it, is not the thing itself. Korzybski held that many people do confuse maps with territories, that is, confuse conceptual models of reality with reality itself. These ideas are crucial to general semantics, a system Korzybski originated.
Mathematical and theoretical biology, or biomathematics, is a branch of biology which employs theoretical analysis, mathematical models and abstractions of living organisms to investigate the principles that govern the structure, development and behavior of the systems, as opposed to experimental biology which deals with the conduction of experiments to test scientific theories. The field is sometimes called mathematical biology or biomathematics to stress the mathematical side, or theoretical biology to stress the biological side. Theoretical biology focuses more on the development of theoretical principles for biology while mathematical biology focuses on the use of mathematical tools to study biological systems, even though the two terms are sometimes interchanged.
Computational sociology is a branch of sociology that uses computationally intensive methods to analyze and model social phenomena. Using computer simulations, artificial intelligence, complex statistical methods, and analytic approaches like social network analysis, computational sociology develops and tests theories of complex social processes through bottom-up modeling of social interactions.
An agent-based model (ABM) is a computational model for simulating the actions and interactions of autonomous agents in order to understand the behavior of a system and what governs its outcomes. It combines elements of game theory, complex systems, emergence, computational sociology, multi-agent systems, and evolutionary programming. Monte Carlo methods are used to understand the stochasticity of these models. Particularly within ecology, ABMs are also called individual-based models (IBMs). A review of recent literature on individual-based models, agent-based models, and multiagent systems shows that ABMs are used in many scientific domains including biology, ecology and social science. Agent-based modeling is related to, but distinct from, the concept of multi-agent systems or multi-agent simulation in that the goal of ABM is to search for explanatory insight into the collective behavior of agents obeying simple rules, typically in natural systems, rather than in designing agents or solving specific practical or engineering problems.
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, to both analyze and visualize the complex connections of these cellular processes.
A complex adaptive system is a system that is complex in that it is a dynamic network of interactions, but the behavior of the ensemble may not be predictable according to the behavior of the components. It is adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events. It is a "complex macroscopic collection" of relatively "similar and partially connected micro-structures" formed in order to adapt to the changing environment and increase their survivability as a macro-structure. The Complex Adaptive Systems approach builds on replicator dynamics.
Simulacra and Simulation is a 1981 philosophical treatise by the philosopher and cultural theorist Jean Baudrillard, in which he seeks to examine the relationships between reality, symbols, and society, in particular the significations and symbolism of culture and media involved in constructing an understanding of shared existence.
Richard Levins was a Marxist biologist, a population geneticist, biomathematician, mathematical ecologist, and philosopher of science who researched diversity in human populations. Until his death, Levins was a university professor at the Harvard T.H. Chan School of Public Health and a long-time political activist. He was best known for his work on evolution and complexity in changing environments and on metapopulations.
Scientific modelling is an activity that produces models representing empirical objects, phenomena, and physical processes, to make a particular part or feature of the world easier to understand, define, quantify, visualize, or simulate. It requires selecting and identifying relevant aspects of a situation in the real world and then developing a model to replicate a system with those features. Different types of models may be used for different purposes, such as conceptual models to better understand, operational models to operationalize, mathematical models to quantify, computational models to simulate, and graphical models to visualize the subject.
Parrondo's paradox, a paradox in game theory, has been described as: A combination of losing strategies becomes a winning strategy. It is named after its creator, Juan Parrondo, who discovered the paradox in 1996. A more explanatory description is:
An ecosystem model is an abstract, usually mathematical, representation of an ecological system, which is studied to better understand the real system.
William Haynes Starbuck graduated from Harvard University and the Carnegie Institute of Technology. He is an organizational scientist who has held professorships in social relations, sociology, business administration, and management.
Artificial life is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry. The discipline was named by Christopher Langton, an American computer scientist, in 1986. In 1987, Langton organized the first conference on the field, in Los Alamos, New Mexico. There are three main kinds of alife, named for their approaches: soft, from software; hard, from hardware; and wet, from biochemistry. Artificial life researchers study traditional biology by trying to recreate aspects of biological phenomena.
"All models are wrong" is a common aphorism and anapodoton in statistics. It is often expanded as "All models are wrong, but some are useful". The aphorism acknowledges that statistical models always fall short of the complexities of reality but can still be useful nonetheless. The aphorism is generally attributed to George E. P. Box, a British statistician, although the underlying concept predates Box's writings.
The Allen Institute is a non-profit, bioscience research institute located in Seattle. It was founded by billionaire philanthropist Paul G. Allen in 2003. The Allen Institute conducts large-scale basic science research studying the brain, cells and immune system in effort to accelerate science and disease research. The organization practices open science, in that they make all their data and resources publicly available for researchers to access.
References
- ↑ "Charles P. Bonini". Stanford Graduate School of Business. Retrieved 28 November 2024.
- ↑ Charles P. Bonini (1963) Simulation of information and decision systems in the firm, Englewood Cliffs, N. J.: Prentice-Hall
- ↑ W. H. Starbuck (1976) Organizations and their environments; In: M. D. Dunnette (ed.), Handbook of Industrial and Organizational Psychology Chicago: Rand, p. 1069-1123
- ↑ Dutton, John M; Starbuck, William H (1971). Computer Simulation of Human Behavior . Wiley. ISBN 0471228508.
- ↑ Valéry, Paul (1942). Mauvaises pensées et autres. Paris: Éditions Gallimard.
- ↑ Valéry, Paul (1970). Collected Works of Paul Valéry, Volume 14, Analects. Translated by Stuart Gilbert. Princeton University Press. p. 466.
- ↑ Levins, Richard (1966). "The strategy of model building in population biology" (PDF). American Scientist . 54 (4): 421–431. JSTOR 27836590. Archived from the original (PDF) on 2 February 2016.
- ↑ Odenbaugh, Jay (15 February 2007). "The strategy of "The strategy of model building in population biology"". Biology & Philosophy. 21 (5): 607–621. doi:10.1007/s10539-006-9049-3. S2CID 171020133.
- ↑ Orzack, Steven Hecht; Sober, Elliott (December 1993). "A Critical Assessment of Levins's The Strategy of Model Building in Population Biology (1966)" (PDF). The Quarterly Review of Biology. 68 (4): 533–546. doi:10.1086/418301. S2CID 83524824.