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Information-theoretic analysis of the dynamics of an executable biological model
- Source :
- PLoS ONE, PLoS ONE, Vol 8, Iss 3, p e59303 (2013)
- Publication Year :
- 2012
-
Abstract
- To facilitate analysis and understanding of biological systems, large-scale data are often integrated into models using a variety of mathematical and computational approaches. Such models describe the dynamics of the biological system and can be used to study the changes in the state of the system over time. For many model classes, such as discrete or continuous dynamical systems, there exist appropriate frameworks and tools for analyzing system dynamics. However, the heterogeneous information that encodes and bridges molecular and cellular dynamics, inherent to fine-grained molecular simulation models, presents significant challenges to the study of system dynamics. In this paper, we present an algorithmic information theory based approach for the analysis and interpretation of the dynamics of such executable models of biological systems. We apply a normalized compression distance (NCD) analysis to the state representations of a model that simulates the immune decision making and immune cell behavior. We show that this analysis successfully captures the essential information in the dynamics of the system, which results from a variety of events including proliferation, differentiation, or perturbations such as gene knock-outs. We demonstrate that this approach can be used for the analysis of executable models, regardless of the modeling framework, and for making experimentally quantifiable predictions. Public Library of Science open access
- Subjects :
- Theoretical computer science
Dynamical systems theory
Clinical Research Design
Information Theory
lcsh:Medicine
02 engineering and technology
Molecular Dynamics Simulation
Information theory
Bioinformatics
Models, Biological
03 medical and health sciences
Lääketieteen bioteknologia - Medical biotechnology
0202 electrical engineering, electronic engineering, information engineering
Humans
lcsh:Science
Biology
Theoretical Biology
Computerized Simulations
030304 developmental biology
Physics
0303 health sciences
Algorithmic information theory
Immunity, Cellular
Multidisciplinary
Systems Biology
Applied Mathematics
lcsh:R
Modeling
Computational Biology
020206 networking & telecommunications
Complex Systems
computer.file_format
Variety (cybernetics)
System dynamics
Normalized compression distance
Computer Science
Medicine
lcsh:Q
State (computer science)
Executable
computer
Algorithms
Mathematics
Research Article
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 8
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- PloS one
- Accession number :
- edsair.doi.dedup.....2d8958076fb0bab6710bd77f2007719e