70,677 research outputs found
DNA Computing by Self-Assembly
Information and algorithms appear to be central to biological organization
and processes, from the storage and reproduction of genetic information to
the control of developmental processes to the sophisticated computations
performed by the nervous system. Much as human technology uses electronic
microprocessors to control electromechanical devices, biological
organisms use biochemical circuits to control molecular and chemical events.
The engineering and programming of biochemical circuits, in vivo and in
vitro, would transform industries that use chemical and nanostructured
materials. Although the construction of biochemical circuits has been
explored theoretically since the birth of molecular biology, our practical
experience with the capabilities and possible programming of biochemical
algorithms is still very young
Information-Theoretic Aspects of Control in a Bio-Hybrid Robot Device
Information processing in natural systems radically differs from current information technology. This difference is particularly apparent in the area of robotics, where both organisms and artificial devices face a similar challenge: the need to act in real time in a complex environment and to do so with computing resources severely limited by their size and power consumption. The formidable gap between artificial and natural systems in terms of information processing capability motivates research into the biological modes of information processing. Such undertakings, however, are hampered by the fact that nature directly exploits the manifold physical characteristics of its computing substrates, while available theoretical tools in general ignore the underlying implementation. Here we sketch the concept of bounded computability in an attempt towards reconciling the information-theoretic perspective with the need to take the material basis of information processing into account. We do so in the context of Physarum polycephalum as a naturally evolved information processor and the use of this organism as an integral component of a robot controller
Chemical communication between synthetic and natural cells: a possible experimental design
The bottom-up construction of synthetic cells is one of the most intriguing
and interesting research arenas in synthetic biology. Synthetic cells are built
by encapsulating biomolecules inside lipid vesicles (liposomes), allowing the
synthesis of one or more functional proteins. Thanks to the in situ synthesized
proteins, synthetic cells become able to perform several biomolecular
functions, which can be exploited for a large variety of applications. This
paves the way to several advanced uses of synthetic cells in basic science and
biotechnology, thanks to their versatility, modularity, biocompatibility, and
programmability. In the previous WIVACE (2012) we presented the
state-of-the-art of semi-synthetic minimal cell (SSMC) technology and
introduced, for the first time, the idea of chemical communication between
synthetic cells and natural cells. The development of a proper synthetic
communication protocol should be seen as a tool for the nascent field of
bio/chemical-based Information and Communication Technologies (bio-chem-ICTs)
and ultimately aimed at building soft-wet-micro-robots. In this contribution
(WIVACE, 2013) we present a blueprint for realizing this project, and show some
preliminary experimental results. We firstly discuss how our research goal
(based on the natural capabilities of biological systems to manipulate chemical
signals) finds a proper place in the current scientific and technological
contexts. Then, we shortly comment on the experimental approaches from the
viewpoints of (i) synthetic cell construction, and (ii) bioengineering of
microorganisms, providing up-to-date results from our laboratory. Finally, we
shortly discuss how autopoiesis can be used as a theoretical framework for
defining synthetic minimal life, minimal cognition, and as bridge between
synthetic biology and artificial intelligence.Comment: In Proceedings Wivace 2013, arXiv:1309.712
Exploring the concept of interaction computing through the discrete algebraic analysis of the Belousov–Zhabotinsky reaction
Interaction computing (IC) aims to map the properties of integrable low-dimensional non-linear dynamical systems to the discrete domain of finite-state automata in an attempt to reproduce in software the self-organizing and dynamically stable properties of sub-cellular biochemical systems. As the work reported in this paper is still at the early stages of theory development it focuses on the analysis of a particularly simple chemical oscillator, the Belousov-Zhabotinsky (BZ) reaction. After retracing the rationale for IC developed over the past several years from the physical, biological, mathematical, and computer science points of view, the paper presents an elementary discussion of the Krohn-Rhodes decomposition of finite-state automata, including the holonomy decomposition of a simple automaton, and of its interpretation as an abstract positional number system. The method is then applied to the analysis of the algebraic properties of discrete finite-state automata derived from a simplified Petri net model of the BZ reaction. In the simplest possible and symmetrical case the corresponding automaton is, not surprisingly, found to contain exclusively cyclic groups. In a second, asymmetrical case, the decomposition is much more complex and includes five different simple non-abelian groups whose potential relevance arises from their ability to encode functionally complete algebras. The possible computational relevance of these findings is discussed and possible conclusions are drawn
Innovation and skill dynamics: a life - cycle approach
This paper focuses on the complementary institutional and organizational adjustments that facilitate the routinization of technological opportunities. To address this issue we propose a life-cycle approach that accounts for the emergence, development and transformation of the conduits for the transmission of new knowledge and skills. While it is widely held that knowledge tends to get more organized as by-product of innovation, the purposeful absorption of practical know-how into formal education is another crucial, and arguably less analysed, intermediate step to bridge the beginning of the life-cycle, when new skills are closely tied to some novel technology, to later phases when the emergence of new disciplines and the diffusion of those skills elicit complementary developments in the technology. The paper connects themes that are central to the tangled policy discourse on skills impact innovation, namely: the institutional adjustments required to favour the re-absorption of skill mismatches; the systematization of knowledge underpinning the creation of new academic disciplines; and implications for dynamics of productivity and of the wage structure.
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