Some computational models at the cellular level

Pathways to cellular supremacy in biocomputing

Synthetic biology uses living cells as the substrate for performing human-defined computations. Many current implementations of cellular computing are based on the “genetic circuit” metaphor, an approximation of the operation of silicon-based computers. Although this conceptual mapping has been relatively successful, we argue that it fundamentally limits the types of computation that may be engineered inside the cell, and fails to exploit the rich and diverse functionality available in natural living systems. We propose the notion of “cellular supremacy” to focus attention on domains in which biocomputing might offer superior performance over traditional computers. We consider potential pathways toward cellular supremacy, and suggest application areas in which it may be found.

Synthetic biology uses cells as its computing substrate, often based on the genetic circuit concept. In this Perspective, the authors argue that existing synthetic biology approaches based on classical models of computation limit the potential of biocomputing, and propose that living organisms have under-exploited capabilities.

A simple computational cell: coupling boolean gene and protein networks

This article presents an abstract, tunable model containing two of the principal information-processing features of cells and explores its use with simulated evolution. The random Boolean model of genetic regulatory networks is extended to include a protein interaction network. The underlying behavior of the resulting two coupled dynamical networks is investigated before their evolvability is explored using a version of the NK model of fitness landscapes.

Taking the example of computer systems engineering for the analysis of biological cell systems

In this paper, we discuss the potential for the use of engineering methods that were originally developed for the design of embedded computer systems, to analyse biological cell systems. For embedded systems as well as for biological cell systems, design is a feature that defines their identity. The assembly of different components in designs of both systems can vary widely. In contrast to the biology domain, the computer engineering domain has the opportunity to quickly evaluate design options and consequences of its systems by methods for computer aided design and in particular design space exploration. We argue that there are enough concrete similarities between the two systems to assume that the engineering methodology from the computer systems domain, and in particular that related to embedded systems, can be applied to the domain of cellular systems. This will help to understand the myriad of different design options cellular systems have. First we compare computer systems with cellular systems. Then, we discuss exactly what features of engineering methods could aid researchers with the analysis of cellular systems, and what benefits could be gained.

Maps, books and other metaphors for systems biology

We briefly review the use of metaphors in science and progressively focus on fields from biology and molecular biology to genomics and bioinformatics. We discuss how metaphors are both a tool for scientific exploration and a medium for public communication of complex subjects, by various short examples. Finally, we propose a metaphor for systems biology that provides an illuminating perspective for the ambitious goals of this field and delimits its current agenda.

Cellulat: an agent-based intracellular signalling model

The theory of behaviour-based systems (or autonomous agents) constitutes a useful approach for the modelling of intracellular signalling networks. In this sense, a cell can be seen as an adaptive autonomous agent or as a society of such agents, where each can exhibit a particular behaviour depending on its cognitive capabilities. We present an intracellular signalling model obtained by integrating several computational techniques into an agent-based paradigm. Cellulat, the model, takes into account two essential aspects of the intracellular signalling networks: (1) cognitive capacities, which are modelled as the agent abilities to interact with the surrounding medium and (2) a spatial organisation, this last obtained using a shared data structure through which the agents communicate between them. We propose a methodology for the modelling of intracellular signalling pathway using Cellulat and we discuss the goal of a virtual laboratory based on our model and presently under development.

Intracellular signalling proteins as smart' agents in parallel distributed processes

In eucaryotic organisms, responses to external signals are mediated by a repertoire of intracellular signalling pathways that ultimately bring about the activation/inactivation of protein kinases and/or protein phosphatases. Until relatively recently, little thought had been given to the intracellular distribution of the components of these signalling pathways. However, experimental evidence from a diverse range of organisms indicates that rather than being freely distributed, many of the protein components of signalling cascades show a significant degree of spatial organisation. Here, we briefly review the roles of 'anchor' 'scaffold' and 'adaptor' proteins in the organisation and functioning of intracellular signalling pathways. We then consider some of the parallel distributed processing capacities of these adaptive systems. We focus on signalling proteins-both as individual 'devices' (agents) and as 'networks' (ecologies) of parallel processes. Signalling proteins are described as 'smart thermodynamic machines' which satisfy 'gluing' (functorial) roles in the information economy of the cell. This combines two information-processing views of signalling proteins. Individually, they show 'cognitive' capacities and collectively they integrate (cohere) cellular processes. We exploit these views by drawing comparisons between signalling proteins and verbs. This text/dialogical metaphor also helps refine our view of signalling proteins as context-sensitive information processing agents.

The organisations of hereditary information

The meaning of hereditary information is not simple. It includes not only what a system receives and transmits but particularly what it makes. The syntactic basis to hereditary information is also not straightforward. For example, is DNA instructions, or data, or both? The answer to this question requires an appreciation of the meaning of the information yet there are a number of possible semantic systems for describing hereditary information including proteins and development. The descriptive boundaries of hereditary information are examined by locating some general organising themes including hierarchy, ecology, regulation, epigenetic systems and talkback. Though metaphors have limits in terms of their explanatory power a number have influenced the development of biological thinking and biosystems have variously been represented as chemical laboratories, computers, electromechanical machines and societies. In this article a further metaphor is discussed, that of life-as-a-play or dance in which the trio of script (genome), cast (metabolism) and stage (cellular structure) co-exist and pre-exist the phenotypic life history which inherits them. A fuller examination of this trio provides an important perspective on the study of the organisations of information processing in hereditary systems.

A mathematical model of neural information processing at the cellular level

The basis for this neuronal model is that the properties of excitable membranes are controlled by biochemical reactions occurring in the nerve cells. The kinetics of these supposed chemical reactions is described by a set of first order differential equations. We considered the effect of regulation of the properties of sodium channels. This allows the simulation of the changes in the neuron's electrical activity parameters occurring during learning, associated with its excitability. The neuronal model exhibits different excitability after the learning procedure relative to the different input signals that corresponds to the experimental data.

The enzymatic basis of information processing in the living cell

Analogies are drawn between the computational aspects of information processing and the enzymatic events of cellular metabolism. The origin thereof is linked to the logic-elements involved in the reaction-diffusion processes of the metabolic operation. It is shown how such function entails a 'molecular machine' quality when associated with organized non-equilibrium energy sources in the cell.

Metaphors, models and bioinformation

The notion of bioinformation is central to the biosciences. This short paper examines a number of metaphors which are intimately related to this idea. These include metaphors about 'system' as well as metaphors associated with biosystem as 'text'. A framework its presented which allows ideas about biosystems and computer systems to be displaced and a number of specific topics are then discussed. Firstly, information processing in non-neural tissues is given as an example of parallel distributed processing. This is followed with a number of metaphors associated with 'text', including 'glue', 'verbs' and 'interpretation'. The paper concludes with a proposal on how to integrate general ideas of bioinformation using the idea of the 'ecology of domains'.