Consideration of mobile DNA: new forms of artificial genetic regulatory networks

Bull, Larry

doi:10.1007/s11047-013-9369-6

Cited by 8 publications

(4 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Analysis of the underlying dynamic connection behavior is as reported above. Fitness drops significantly for higher B, as seen in the RBNK model with and without the structural dynamism previously used [2], and also in the RBNKCS model of multicellularity with and without that form of structural dynamism [3,4].…”

Section: Multicellularitymentioning

confidence: 84%

Evolving Functional and Structural Dynamism in Coupled Boolean Networks

Bull

2014

Artificial Life

Self Cite

View full text Add to dashboard Cite

This article uses a recently presented abstract, tunable Boolean regulatory network model to further explore aspects of mobile DNA, such as transposons. The significant role of mobile DNA in the evolution of natural systems is becoming increasingly clear. This article shows how dynamically controlling network node connectivity and function via transposon-inspired mechanisms can be selected for to significant degrees under coupled regulatory network scenarios, including when such changes are heritable. Simple multicellular and coevolutionary versions of the model are considered.

show abstract

Section: Multicellularitymentioning

confidence: 84%

Evolving Functional and Structural Dynamism in Coupled Boolean Networks

Bull

2014

Artificial Life

Self Cite

View full text Add to dashboard Cite

show abstract

“…Further consideration of epigenetic control suggests a number of extensions to this work in the near future, particularly in conjunction with the use of mobile DNA inspired mechanisms (e.g., see [Bull, 2013]). Future work should also consider the use of epigenetic control within other GRN representations, explore whether these results also hold for asynchronous GRN updating schemes, and determine whether the general results also appear to be true for much larger multicellular systems, i.e., for S>>1.…”

Section: Discussionmentioning

confidence: 99%

Evolving Boolean regulatory networks with epigenetic control

Bull

2014

Biosystems

Self Cite

View full text Add to dashboard Cite

The significant role of epigenetic mechanisms within natural systems has become increasingly clear. This paper uses a recently presented abstract, tunable Boolean genetic regulatory network model to explore aspects of epigenetics. It is shown how dynamically controlling transcription via a DNA methylation-inspired mechanism can be selected for by simulated evolution under various single and multiple cell scenarios. Further, it is shown that the effects of such control can be inherited without detriment to fitness.

show abstract

“…This was effective at certain tasks, which benefited from decomposition; however, the complexity and appropriate parameterization of the system was a significant issue. Self-modification was also explored in [31] within the context of a model of mobile DNA applied to Boolean networks, in which the author found it to be beneficial in terms of access and stability of attractors. We have also explored a simpler model of chromatin remodeling in which subtasks are prespecified [8], and published initial results using the current approach [9] which have been significantly extended in this paper.…”

Section: Self-modification In Artificial Biochemical Networkmentioning

confidence: 99%

Artificial Epigenetic Networks: Automatic Decomposition of Dynamical Control Tasks Using Topological Self-Modification

Turner

Caves

Stepney

et al. 2017

IEEE Trans. Neural Netw. Learning Syst.

View full text Add to dashboard Cite

This paper describes the artificial epigenetic network, a recurrent connectionist architecture that is able to dynamically modify its topology in order to automatically decompose and solve dynamical problems. The approach is motivated by the behavior of gene regulatory networks, particularly the epigenetic process of chromatin remodeling that leads to topological change and which underlies the differentiation of cells within complex biological organisms. We expected this approach to be useful in situations where there is a need to switch between different dynamical behaviors, and do so in a sensitive and robust manner in the absence of a priori information about problem structure. This hypothesis was tested using a series of dynamical control tasks, each requiring solutions that could express different dynamical behaviors at different stages within the task. In each case, the addition of topological self-modification was shown to improve the performance and robustness of controllers. We believe this is due to the ability of topological changes to stabilize attractors, promoting stability within a dynamical regime while allowing rapid switching between different regimes. Post hoc analysis of the controllers also demonstrated how the partitioning of the networks could provide new insights into problem structure.

show abstract

Consideration of mobile DNA: new forms of artificial genetic regulatory networks

Cited by 8 publications

References 32 publications

Evolving Functional and Structural Dynamism in Coupled Boolean Networks

Evolving Functional and Structural Dynamism in Coupled Boolean Networks

Evolving Boolean regulatory networks with epigenetic control

Artificial Epigenetic Networks: Automatic Decomposition of Dynamical Control Tasks Using Topological Self-Modification

Contact Info

Product

Resources

About