46,289 research outputs found
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
Recommended from our members
Synthetic biology: advancing biological frontiers by building synthetic systems
Advances in synthetic biology are contributing
to diverse research areas, from basic biology to
biomanufacturing and disease therapy. We discuss the
theoretical foundation, applications, and potential of
this emerging field
Modeling Life as Cognitive Info-Computation
This article presents a naturalist approach to cognition understood as a
network of info-computational, autopoietic processes in living systems. It
provides a conceptual framework for the unified view of cognition as evolved
from the simplest to the most complex organisms, based on new empirical and
theoretical results. It addresses three fundamental questions: what cognition
is, how cognition works and what cognition does at different levels of
complexity of living organisms. By explicating the info-computational character
of cognition, its evolution, agent-dependency and generative mechanisms we can
better understand its life-sustaining and life-propagating role. The
info-computational approach contributes to rethinking cognition as a process of
natural computation in living beings that can be applied for cognitive
computation in artificial systems.Comment: Manuscript submitted to Computability in Europe CiE 201
Causality, Information and Biological Computation: An algorithmic software approach to life, disease and the immune system
Biology has taken strong steps towards becoming a computer science aiming at
reprogramming nature after the realisation that nature herself has reprogrammed
organisms by harnessing the power of natural selection and the digital
prescriptive nature of replicating DNA. Here we further unpack ideas related to
computability, algorithmic information theory and software engineering, in the
context of the extent to which biology can be (re)programmed, and with how we
may go about doing so in a more systematic way with all the tools and concepts
offered by theoretical computer science in a translation exercise from
computing to molecular biology and back. These concepts provide a means to a
hierarchical organization thereby blurring previously clear-cut lines between
concepts like matter and life, or between tumour types that are otherwise taken
as different and may not have however a different cause. This does not diminish
the properties of life or make its components and functions less interesting.
On the contrary, this approach makes for a more encompassing and integrated
view of nature, one that subsumes observer and observed within the same system,
and can generate new perspectives and tools with which to view complex diseases
like cancer, approaching them afresh from a software-engineering viewpoint that
casts evolution in the role of programmer, cells as computing machines, DNA and
genes as instructions and computer programs, viruses as hacking devices, the
immune system as a software debugging tool, and diseases as an
information-theoretic battlefield where all these forces deploy. We show how
information theory and algorithmic programming may explain fundamental
mechanisms of life and death.Comment: 30 pages, 8 figures. Invited chapter contribution to Information and
Causality: From Matter to Life. Sara I. Walker, Paul C.W. Davies and George
Ellis (eds.), Cambridge University Pres
Modelling of Multi-Agent Systems: Experiences with Membrane Computing and Future Challenges
Formal modelling of Multi-Agent Systems (MAS) is a challenging task due to
high complexity, interaction, parallelism and continuous change of roles and
organisation between agents. In this paper we record our research experience on
formal modelling of MAS. We review our research throughout the last decade, by
describing the problems we have encountered and the decisions we have made
towards resolving them and providing solutions. Much of this work involved
membrane computing and classes of P Systems, such as Tissue and Population P
Systems, targeted to the modelling of MAS whose dynamic structure is a
prominent characteristic. More particularly, social insects (such as colonies
of ants, bees, etc.), biology inspired swarms and systems with emergent
behaviour are indicative examples for which we developed formal MAS models.
Here, we aim to review our work and disseminate our findings to fellow
researchers who might face similar challenges and, furthermore, to discuss
important issues for advancing research on the application of membrane
computing in MAS modelling.Comment: In Proceedings AMCA-POP 2010, arXiv:1008.314
Roadmap on semiconductor-cell biointerfaces.
This roadmap outlines the role semiconductor-based materials play in understanding the complex biophysical dynamics at multiple length scales, as well as the design and implementation of next-generation electronic, optoelectronic, and mechanical devices for biointerfaces. The roadmap emphasizes the advantages of semiconductor building blocks in interfacing, monitoring, and manipulating the activity of biological components, and discusses the possibility of using active semiconductor-cell interfaces for discovering new signaling processes in the biological world
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