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What is Complex Systems

Chapter 22
Handbook of Research on Computational Methodologies in Gene Regulatory Networks
are said to be systems of interacting components with no central control that display emergent global properties not present at the components level.
Published in Chapter:
A Model for a Heterogeneous Genetic Network
Ângela T.F. Gonçalves (Darwin College, UK) and Ernesto J.F. Costa (Pólo II- Pinhal de Marrocos, Portugal)
Copyright: © 2010 |Pages: 23
DOI: 10.4018/978-1-60566-685-3.ch022
Abstract
In this chapter, we propose a new model for gene regulatory networks (GRN). The model incorporates more biological detail than other approaches, and is based on an artificial genome from which several products like genes, mRNA, miRNA, noncoding RNA, and proteins are extracted and connected, giving rise to a heterogeneous directed graph. We study the dynamics of the networks thus obtained, along with their topology (using degree distributions). Some considerations are made about the biological meaning of the outcome of the simulations.
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Chapter 72
Exploring Information Security Risks in Healthcare Systems
Systems that interweave components in such a way that they display variation without being random, and result in a structure that is more than the sum of its parts.
Published in Chapter: Exploring Information Security Risks in Healthcare Systems; From: Encyclopedia of Healthcare Information Systems
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Chapter 7
Multi-Scale, Multi-Dimensional Modelling of Future Energy Systems
A system made up of a number of connected objects, which shows a number of properties which include nonlinearity, emergence and interactions – often these systems are referred to as complex adaptive systems.
Published in Chapter: Multi-Scale, Multi-Dimensional Modelling of Future Energy Systems; From: Handbook of Research on Social, Economic, and Environmental Sustainability in the Development of Smart Cities
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Chapter 83
Querical Data Networks
Complex Systems is a new field of science studying how parts of a complex system give rise to the collective behaviors of the system. Complexity (information-theoretical and computational) and emergence of collective behavior are the two main characteristics of such complex systems. Social systems formed (in part) out of people, the brain formed out of neurons, molecules formed out of atoms, the weather formed out of air flows are all examples of complex systems. The field of Complex Systems cuts across all traditional disciplines of science, as well as engineering, management, and medicine.
Published in Chapter: Querical Data Networks; From: Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends
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Chapter 1
An Agent-Based Approach to Designing VO
Refer to systems that are composed of a (large) number of parts that interact in a non-simple way and where the whole is more than the sum of the parts, and that does not have pure superposition of phenomena and processes.
Published in Chapter: An Agent-Based Approach to Designing VO; From: Encyclopedia of Networked and Virtual Organizations
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Chapter 122
Measures of Network Structure
Network-based systems characterized by feedback-driven flow of information, openness, self-organization, and emergence.
Published in Chapter: Measures of Network Structure; From: Encyclopedia of Networked and Virtual Organizations
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Chapter 16
Five Insights for Change Managers in Second-Order Change. Organizations as Complex Systems
An organizational system in which agents act locally with each other based on an identity that has developed historically; they do this without knowing how the whole system will develop further and without an understanding of the current state of the system as a whole.
Published in Chapter: Five Insights for Change Managers in Second-Order Change. Organizations as Complex Systems; From: Handbook of Research on Chaos and Complexity Theory in the Social Sciences
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Chapter 156
Mathematical Modeling of Artificial Neural Networks
Systems made of several interconnected simple parts which altogether exhibit a high degree of complexity from each emerges a higher order behaviour.
Published in Chapter: Mathematical Modeling of Artificial Neural Networks; From: Encyclopedia of Artificial Intelligence
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