74,222 research outputs found
P Systems based Computing Polynomials: Design and Formal Verification
Automatic design of P systems is an attractive research topic
in the community of membrane computing. Differing from the previous
work that used evolutionary algorithms to fulfill the task, this paper
presents the design of a simple (deterministic transition) P system
(without input membrane) of degree 1, capturing the value of the k-
order (k 2) polynomial by using a reasoning method. Specifically, the
values of polynomial p(n) corresponding to a natural number t is equal
to the multiplicity of a distinguished object of the system (the output
object) in the configuration at instant t. We also discuss the descriptive
computational resources required by the designed k-order polynomial P
system.Ministerio de EconomĂa y Competitividad TIN2012-3743
Synthetic Gene Circuits: Design with Directed Evolution
Synthetic circuits offer great promise for generating insights into nature's underlying design principles or forward engineering novel biotechnology applications. However, construction of these circuits is not straightforward. Synthetic circuits generally consist of components optimized to function in their natural context, not in the context of the synthetic circuit. Combining mathematical modeling with directed evolution offers one promising means for addressing this problem. Modeling identifies mutational targets and limits the evolutionary search space for directed evolution, which alters circuit performance without the need for detailed biophysical information. This review examines strategies for integrating modeling and directed evolution and discusses the utility and limitations of available methods
Early evolution of purple retinal pigments on Earth and implications for exoplanet biosignatures
We propose that retinal-based phototrophy arose early in the evolution of
life on Earth, profoundly impacting the development of photosynthesis and
creating implications for the search for life beyond our planet. While the
early evolutionary history of phototrophy is largely in the realm of the
unknown, the onset of oxygenic photosynthesis in primitive cyanobacteria
significantly altered the Earth's atmosphere by contributing to the rise of
oxygen ~2.3 billion years ago. However, photosynthetic chlorophyll and
bacteriochlorophyll pigments lack appreciable absorption at wavelengths about
500-600 nm, an energy-rich region of the solar spectrum. By contrast, simpler
retinal-based light-harvesting systems such as the haloarchaeal purple membrane
protein bacteriorhodopsin show a strong well-defined peak of absorbance
centered at 568 nm, which is complementary to that of chlorophyll pigments. We
propose a scenario where simple retinal-based light-harvesting systems like
that of the purple chromoprotein bacteriorhodopsin, originally discovered in
halophilic Archaea, may have dominated prior to the development of
photosynthesis. We explore this hypothesis, termed the 'Purple Earth,' and
discuss how retinal photopigments may serve as remote biosignatures for
exoplanet research.Comment: Published Open Access in the International Journal of Astrobiology;
10 pages, 6 figure
Enaction-Based Artificial Intelligence: Toward Coevolution with Humans in the Loop
This article deals with the links between the enaction paradigm and
artificial intelligence. Enaction is considered a metaphor for artificial
intelligence, as a number of the notions which it deals with are deemed
incompatible with the phenomenal field of the virtual. After explaining this
stance, we shall review previous works regarding this issue in terms of
artifical life and robotics. We shall focus on the lack of recognition of
co-evolution at the heart of these approaches. We propose to explicitly
integrate the evolution of the environment into our approach in order to refine
the ontogenesis of the artificial system, and to compare it with the enaction
paradigm. The growing complexity of the ontogenetic mechanisms to be activated
can therefore be compensated by an interactive guidance system emanating from
the environment. This proposition does not however resolve that of the
relevance of the meaning created by the machine (sense-making). Such
reflections lead us to integrate human interaction into this environment in
order to construct relevant meaning in terms of participative artificial
intelligence. This raises a number of questions with regards to setting up an
enactive interaction. The article concludes by exploring a number of issues,
thereby enabling us to associate current approaches with the principles of
morphogenesis, guidance, the phenomenology of interactions and the use of
minimal enactive interfaces in setting up experiments which will deal with the
problem of artificial intelligence in a variety of enaction-based ways
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Opposing Pressures of Speed and Efficiency Guide the Evolution of Molecular Machines.
Many biomolecular machines need to be both fast and efficient. How has evolution optimized these machines along the tradeoff between speed and efficiency? We explore this question using optimizable dynamical models along coordinates that are plausible evolutionary degrees of freedom. Data on 11 motors and ion pumps are consistent with the hypothesis that evolution seeks an optimal balance of speed and efficiency, where any further small increase in one of these quantities would come at great expense to the other. For FoF1-ATPases in different species, we also find apparent optimization of the number of subunits in the c-ring, which determines the number of protons pumped per ATP synthesized. Interestingly, these ATPases appear to more optimized for efficiency than for speed, which can be rationalized through their key role as energy transducers in biology. The present modeling shows how the dynamical performance properties of biomolecular motors and pumps may have evolved to suit their corresponding biological actions
The Jackprot Simulation Couples Mutation Rate with Natural Selection to Illustrate How Protein Evolution Is Not Random
Protein evolution is not a random process. Views which attribute randomness to molecular change, deleterious nature to single-gene mutations, insufficient geological time, or population size for molecular improvements to occur, or invoke âdesign creationismâ to account for complexity in molecular structures and biological processes, are unfounded. Scientific evidence suggests that natural selection tinkers with molecular improvements by retaining adaptive peptide sequence. We used slot-machine probabilities and ion channels to show biological directionality on molecular change. Because ion channels reside in the lipid bilayer of cell membranes, their residue location must be in balance with the membraneâs hydrophobic/philic nature; a selective âporeâ for ion passage is located within the hydrophobic region. We contrasted the random generation of DNA sequence for KcsA, a bacterial two-transmembrane-domain (2TM) potassium channel, from Streptomyces lividans, with an under-selection scenario, the âjackprot,â which predicted much faster evolution than by chance. We wrote a computer program in JAVA APPLET version 1.0 and designed an online interface, The Jackprot Simulation http://faculty.rwu.edu/cbai/JackprotSimulation.htm, to model a numerical interaction between mutation rate and natural selection during a scenario of polypeptide evolution. Winning the âjackprot,â or highest-fitness complete-peptide sequence, required cumulative smaller âwinsâ (rewarded by selection) at the first, second, and third positions in each of the 161 KcsA codons (âjackdonsâ that led to âjackacidsâ that led to the âjackprotâ). The âjackprotâ is a didactic tool to demonstrate how mutation rate coupled with natural selection suffices to explain the evolution of specialized proteins, such as the complex six-transmembrane (6TM) domain potassium, sodium, or calcium channels. Ancestral DNA sequences coding for 2TM-like proteins underwent nucleotide âeditionâ and gene duplications to generate the 6TMs. Ion channels are essential to the physiology of neurons, ganglia, and brains, and were crucial to the evolutionary advent of consciousness. The Jackprot Simulation illustrates in a computer model that evolution is not and cannot be a random process as conceived by design creationists
Receptor uptake arrays for vitamin B12, siderophores and glycans shape bacterial communities
Molecular variants of vitamin B12, siderophores and glycans occur. To take up
variant forms, bacteria may express an array of receptors. The gut microbe
Bacteroides thetaiotaomicron has three different receptors to take up variants
of vitamin B12 and 88 receptors to take up various glycans. The design of
receptor arrays reflects key processes that shape cellular evolution.
Competition may focus each species on a subset of the available nutrient
diversity. Some gut bacteria can take up only a narrow range of carbohydrates,
whereas species such as B.~thetaiotaomicron can digest many different complex
glycans. Comparison of different nutrients, habitats, and genomes provide
opportunity to test hypotheses about the breadth of receptor arrays. Another
important process concerns fluctuations in nutrient availability. Such
fluctuations enhance the value of cellular sensors, which gain information
about environmental availability and adjust receptor deployment. Bacteria often
adjust receptor expression in response to fluctuations of particular
carbohydrate food sources. Some species may adjust expression of uptake
receptors for specific siderophores. How do cells use sensor information to
control the response to fluctuations? That question about regulatory wiring
relates to problems that arise in control theory and artificial intelligence.
Control theory clarifies how to analyze environmental fluctuations in relation
to the design of sensors and response systems. Recent advances in deep learning
studies of artificial intelligence focus on the architecture of regulatory
wiring and the ways in which complex control networks represent and classify
environmental states. I emphasize the similar design problems that arise in
cellular evolution, control theory, and artificial intelligence. I connect
those broad concepts to testable hypotheses for bacterial uptake of B12,
siderophores and glycans.Comment: Added many new references, edited throughou
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