Skip Nav Destination
1-5 of 5
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
. isal, ALIFE 2022: The 2022 Conference on Artificial Life70, (July 18–22, 2022) doi: 10.1162/isal_a_00500
This paper describes a potentially rewarding research program aimed at designing, modeling, analyzing and experimentally realizing artificial cells in the wetware domain endowed with a ‘neural network’-like module for achieving minimal perception. In particular, we present a possible implementation based on bacterial phosphorylation signaling networks (dubbed as “phospho-neural network” by Hellingwerf and collaborators in 1995 ). At this initial stage only preliminary discussions are possible. The scenario we devise minimizes unrealistic assumptions and it is based on the state-of-the-art of contemporary artificial cell technology. This contribution is intended as a plan to forster the construction and the theoretical analysis of next-generation artificial cells.
. isal2019, ALIFE 2019: The 2019 Conference on Artificial Life211-217, (July 29–August 2, 2019) doi: 10.1162/isal_a_00163
Cellular types of multicellular organisms are the stable results of complex intertwined processes that occur in biological cells. Among the many others, chromatin dynamics significantly contributes—by modulating access to genes—to differential gene expression, and ultimately to determine cell types. Here, we propose a dynamical model of differentiation based on a simplified bio-inspired methylation mechanism in Boolean models of GRNs. Preliminary results show that, as the number of methylated nodes increases, there is a decrease in attractor number and networks tend to assume dynamical behaviours typical of ordered ensembles. At the same time, results show that this mechanism does not affect the possibility of generating path dependent differentiation: cell types determined by the specific sequence of methylated genes.
. ecal2017, ECAL 2017, the Fourteenth European Conference on Artificial Life370-371, (September 4–8, 2017) doi: 10.1162/isal_a_063
The detection of critical states is a task of utmost importance in complex systems; to this aim, measures to identify such conditions are required. In general, the term criticality concerns the existence of two qualitatively different behaviours that a system can exhibit, which depends on some parameter values. In this short communication, we summarise our recent findings on the use of the Relevance Index to identify critical states in complex systems. Although the Relevance Index method was originally developed to identify relevant sets of variables in dynamical systems, we show that it is also able to detect features of criticality. The index is applied to two notable examples showing slightly different meanings of criticality, namely, the Ising model and Random Boolean Networks. Results show that this index is maximised at critical states and is robust with respect to system size and sampling effort.
Exploring the organisation of complex systems through the dynamical interactions among their relevant subsets
. ecal2015, ECAL 2015: the 13th European Conference on Artificial Life286-293, (July 20–24, 2015) doi: 10.1162/978-0-262-33027-5-ch054
Boolean Network Robotics as an Intermediate Step in the Synthesis of Finite State Machines for Robot Control
. ecal2013, ECAL 2013: The Twelfth European Conference on Artificial Life783-790, (September 2–6, 2013) doi: 10.1162/978-0-262-31709-2-ch112