In this paper, we investigate the problem of reverse engineering the topology of gene regulatory networks from temporal gene expression data. We adopt a computational intelligence approach comprising swarm intelligence techniques, namely particle swarm optimization (PSO) and ant colony optimization (ACO). In addition, the recurrent neural network (RNN) formalism is employed for modeling the dynamical behavior of gene regulatory systems. More specifically, ACO is used for searching the discrete space of network architectures and PSO for searching the corresponding continuous space of RNN model parameters. We propose a novel solution construction process in the context of ACO for generating biologically plausible candidate architectures. The objective is to concentrate the search effort into areas of the structure space that contain architectures which are feasible in terms of their topological resemblance to real-world networks. The proposed framework is initially applied to the reconstruction of a small artificial network that has previously been studied in the context of gene network reverse engineering. Subsequently, we consider an artificial data set with added noise for reconstructing a subnetwork of the genetic interaction network of S. cerevisiae (yeast). Finally, the framework is applied to a real-world data set for reverse engineering the SOS response system of the bacterium Escherichia coli. Results demonstrate the relative advantage of utilizing problem-specific knowledge regarding biologically plausible structural properties of gene networks over conducting a problem-agnostic search in the vast space of network architectures.
The repression of competition by mechanisms of policing is now recognized as a major force in the maintenance of cooperation. General models on the evolution of policing have focused on the interplay between individual competitiveness and mutual policing, demonstrating a positive relationship between within-group diversity and levels of policing. We expand this perspective by investigating what is possibly the simplest example of reproductive policing: copy number control (CNC) among non-conjugative plasmids, a class of extra-chromosomal vertically transmitted molecular symbionts of bacteria. Through the formulation and analysis of a multi-scale dynamical model, we show that the establishment of stable reproductive restraint among plasmids requires the co-evolution of two fundamental plasmid traits: policing, through the production of plasmid-coded trans-acting replication inhibitors, and obedience, expressed as the binding affinity of plasmid-specific targets to those inhibitors. We explain the intrinsic replication instabilities that arise in the absence of policing and we show how these instabilities are resolved by the evolution of copy number control. Increasing levels of policing and obedience lead to improvements in group performance due to tighter control of local population size (plasmid copy number), delivering benefits both to plasmids, by reducing the risk of segregational loss and to the plasmid-host partnership, by increasing the rate of cell reproduction, and therefore plasmid vertical transmission.
In this paper, we propose an alternative strategy of adapting the inertia weight parameter during the course of particle swarm optimization, by means of a non-monotonic inertia weight function of time. Results demonstrate that an oscillating inertia weight function is competitive and in some cases better than established inertia weight functions, in terms of consistency and speed of convergence.
Policing is a widespread mechanism regulating cooperation in both human and animal social groups.Policing can promote the evolution and maintenance of cooperation among non-relatives by tying the reproductive success of individuals to the efficiency and success of the group. In this paper, we investigate the evolution of reproductive policing using a multi-scale computational model inspired by the copy number control system of conjugative bacterial plasmids. Our results show that the repression of competition through policing can evolve across a very broad range of migration (plasmid conjugation) rates, improving system-level performance and bringing efficiency gains to the group beyond those achievable by pure self-restraint. Reproductive policing acts to increase genetic relatedness by reducing variation in group size which, in turn, reduces the heterogeneity of the plasmid population. When among-group migration is high, coercive policing strategies are favoured, characterized by high levels of policing coupled with relatively lower obedience. Coercive policing strategies preferentially limit the reproduction of rival lineages while, at the same time, maintaining effective collective reproductive control. Author SummaryThe emergence and maintenance of cooperation is a topic of great importance in evolutionary biology.The evolution of cooperation has been explained in the context of kin selection when there is sufficient genetic relatedness among interacting individuals. When there is insufficient relatedness, the presence of alternative mechanisms, such as mutual policing, can promote the evolution and maintenance of cooperation by tying the reproductive success of individual to the efficiency and success of the group. In this paper, we investigate the evolution of reproductive policing using an agent-based computational model inspired by a simple and elegant biological example: replication control among conjugative plasmids, a class . CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/053579 doi: bioRxiv preprint first posted online May. 22, 2016; 2 of molecular symbionts of bacterial hosts. Our results show that the repression of competition through policing evolves and improves plasmid group performance beyond levels achievable by self-restraint, across a very broad range of migration rates. Under conditions of high migration (frequent conjugation), we observe the evolution of coercive policing strategies that limit the reproduction of rival lineages by investing disproportionately in policing relative to their obedience to the policing trait.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.