Elucidation of T cell signalling models

Owens, Nick; Timmis, Jon; Greensted, Andrew; Tyrrell, Andy M.

doi:10.1016/j.jtbi.2009.10.017

Cited by 10 publications

(3 citation statements)

References 24 publications

(94 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results can be directly applied to study yet unknown aspects of auto-immune reactions and other dysfunctions. Also, the influence of specific proteins and their influence can be predicted [23].…”

Section: A Investigation Of Artificial Modelsmentioning

confidence: 99%

Bio-inspired networking: from theory to practice

2010

View full text Add to dashboard Cite

Abstract-Bio-inspired networking techniques have been investigated since more than a decade. Findings in this field have fostered new developments in networking, especially in the most challenging domains such as handling large scale networks, their dynamic nature, resource constraints, heterogeneity, unattended operation, and robustness. Even though this new research area started with highly theoretical concepts, it can be seen that there is also practical impact. This article aims to give an overview to the general field of bio-inspired networking, introducing the key concepts and methodologies. Selected examples that outline the capabilities and the practical relevance are discussed in more detail. The presented examples outline the activities of a new community working on bio-inspired networking solutions, which is converging and becomes visible in term of the provided astonishingly efficient solutions.

show abstract

Section: A Investigation Of Artificial Modelsmentioning

confidence: 99%

Bio-inspired networking: from theory to practice

2010

View full text Add to dashboard Cite

show abstract

“…The total concentration of complexes ([AB total ]) can be obtained by adding (5) and the summation of all the other complexes concentrations using (6):…”

Section: Classical Kinetic Proofreadingmentioning

confidence: 99%

Tunable kinetic proofreading in a model with molecular frustration

2011

View full text Add to dashboard Cite

Abstract. In complex systems, feedback loops can build intricate emergent phenomena, so that a description of the whole system cannot be easily derived from the properties of the individual parts. Here we propose that inter-molecular frustration mechanisms can provide non trivial feedback loops which can develop nontrivial specificity amplification. We show that this mechanism can be seen as a more general form of a kinetic proofreading mechanism, with an interesting new property, namely the ability to tune the specificity amplification by changing the reactants concentrations. This contrasts with the classical kinetic proofreading mechanism in which specificity is a function of only the reaction rate constants involved in a chemical pathway. These results are also interesting because they show that a wide class of frustration models exists that share the same underlining kinetic proofreading mechanisms, with even richer properties. These models can find applications in different areas such as evolutionary biology, immunology and biochemistry.

show abstract

“…A few notable exceptions exist. Owens et al [10,11] refer to biological literature in Phase 1 of the framework, then show how models of T-cell receptor signalling, developed and validated in Phase 2, can be used to derive a Kernel Density Estimation method for anomaly detection. Andrews [12] evaluates the framework itself in his PhD, first examining immunological literature for inspiration, then building models of a receptor degeneracy which inspire the creation of a pattern classification algorithm.…”

Section: Introductionmentioning

confidence: 99%

An Engineering-Informed Modelling Approach to AIS

Hart

Davoudani

2011

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. A recent shift in thinking in Artificial Immune Systems (AIS) advocates developing a greater understanding of the underlying biological systems that serve as inspiration for engineering such systems by developing abstract computational models of the immune system in order to better understand the natural biology. We propose a refinement to existing frameworks which requires development of such models to be driven by the engineering problem being considered; the constraints of the engineered system must inform not only the model development, but also its validation. Using a case-study, we present a methodology which enables an abstract model of dendritic-cell trafficking to be developed with the purpose of building a self-organising wireless sensor network for temperature monitoring and maintenance. The methodology enables the development of a model which is consistent with the application constraints from the outset and can be validated in terms of the functional requirements of the application. Although the result models are not likely to be biologically faithful, they enable the engineer to better exploit the underlying metaphor, ultimately leading to reduced development time of the engineered system.

show abstract

Elucidation of T cell signalling models

Cited by 10 publications

References 24 publications

Bio-inspired networking: from theory to practice

Bio-inspired networking: from theory to practice

Tunable kinetic proofreading in a model with molecular frustration

An Engineering-Informed Modelling Approach to AIS

Contact Info

Product

Resources

About