3,260 research outputs found
Notes on stochastic (bio)-logic gates: the role of allosteric cooperativity
Recent experimental breakthroughs have finally allowed to implement in-vitro
reaction kinetics (the so called {\em enzyme based logic}) which code for
two-inputs logic gates and mimic the stochastic AND (and NAND) as well as the
stochastic OR (and NOR). This accomplishment, together with the already-known
single-input gates (performing as YES and NOT), provides a logic base and paves
the way to the development of powerful biotechnological devices. The
investigation of this field would enormously benefit from a self-consistent,
predictive, theoretical framework. Here we formulate a complete statistical
mechanical description of the Monod-Wyman-Changeaux allosteric model for both
single and double ligand systems, with the purpose of exploring their practical
capabilities to express logical operators and/or perform logical operations.
Mixing statistical mechanics with logics, and quantitatively our findings with
the available biochemical data, we successfully revise the concept of
cooperativity (and anti-cooperativity) for allosteric systems, with particular
emphasis on its computational capabilities, the related ranges and scaling of
the involved parameters and its differences with classical cooperativity (and
anti-cooperativity)
Combinatorial Control through Allostery
Many instances of cellular signaling and transcriptional regulation involve
switch-like molecular responses to the presence or absence of input ligands. To
understand how these responses come about and how they can be harnessed, we
develop a statistical mechanical model to characterize the types of Boolean
logic that can arise from allosteric molecules following the
Monod-Wyman-Changeux (MWC) model. Building upon previous work, we show how an
allosteric molecule regulated by two inputs can elicit AND, OR, NAND and NOR
responses, but is unable to realize XOR or XNOR gates. Next, we demonstrate the
ability of an MWC molecule to perform ratiometric sensing - a response behavior
where activity depends monotonically on the ratio of ligand concentrations. We
then extend our analysis to more general schemes of combinatorial control
involving either additional binding sites for the two ligands or an additional
third ligand and show how these additions can cause a switch in the logic
behavior of the molecule. Overall, our results demonstrate the wide variety of
control schemes that biological systems can implement using simple mechanisms
From Cognition to Consciousness:\ud a discussion about learning, reality representation and decision making.
The scientific understanding of cognition and consciousness is currently hampered by the lack of rigorous and universally accepted definitions that permit comparative studies. This paper proposes new functional and un- ambiguous definitions for cognition and consciousness in order to provide clearly defined boundaries within which general theories of cognition and consciousness may be developed. The proposed definitions are built upon the construction and manipulation of reality representation, decision making and learning and are scoped in terms of an underlying logical structure. It is argued that the presentation of reality also necessitates the concept of ab- sence and the capacity to perform transitive inference. Explicit predictions relating to these new definitions, along with possible ways to test them, are also described and discussed
Boolean versus continuous dynamics on simple two-gene modules
We investigate the dynamical behavior of simple modules composed of two genes
with two or three regulating connections. Continuous dynamics for mRNA and
protein concentrations is compared to a Boolean model for gene activity. Using
a generalized method, we study within a single framework different continuous
models and different types of regulatory functions, and establish conditions
under which the system can display stable oscillations. These conditions
concern the time scales, the degree of cooperativity of the regulating
interactions, and the signs of the interactions. Not all models that show
oscillations under Boolean dynamics can have oscillations under continuous
dynamics, and vice versa.Comment: 8 pages, 10 figure
A Uniform Mathematical Representation of Logic and Computation.
The current models of computation share varying levels of correspondence with actual implementation schemes. They can be arranged in a hierarchical structure depending upon their level of abstraction. In classical computing, the circuit model shares closest correspondence with physical implementation, followed by finite automata techniques. The highest level in the abstraction hierarchy is that of the theory of computation.Likewise, there exist computing paradigms based upon a different set of defining principles. The classical paradigm involves computing as has been applied traditionally, and is characterized by Boolean circuits that are irreversible in nature. The reversible paradigm requires invertible primitives in order to perform computation. The paradigm of quantum computing applies the theory of quantum mechanics to perform computational tasks.Our analysis concludes that descriptions at lowest level in the abstraction hierarchy should be uniform across the three paradigms, but the same is not true in case of current descriptions. We propose a mathematical representation of logic and computation that successfully explains computing models in all three paradigms, while making a seamless transition to higher levels of the abstraction hierarchy. This representation is based upon the theory of linear spaces and, hence, is referred to as the linear representation. The representation is first developed in the classical context, followed by an extension to the reversible paradigm by exploiting the well-developed theory on invertible mappings. The quantum paradigm is reconciled with this representation through correspondence that unitary operators share with the proposed linear representation. In this manner, the representation is shown to account for all three paradigms. The correspondence shared with finite automata models is also shown to hold implicitly during the development of this representation. Most importantly, the linear representation accounts for the Hamiltonians that define the dynamics of a computational process, thereby resolving the correspondence shared with underlying physical principles.The consistency of the linear representation is checked against a current existing application in VLSI CAD that exploits the linearity of logic functions for symbolic representation of circuits. Some possible applications and applicability of the linear representation to some open problems are also discussed
LOT: Logic Optimization with Testability - new transformations for logic synthesis
A new approach to optimize multilevel logic circuits is introduced. Given a multilevel circuit, the synthesis method optimizes its area while simultaneously enhancing its random pattern testability. The method is based on structural transformations at the gate level. New transformations involving EX-OR gates as well as Reed–Muller expansions have been introduced in the synthesis of multilevel circuits. This method is augmented with transformations that specifically enhance random-pattern testability while reducing the area. Testability enhancement is an integral part of our synthesis methodology. Experimental results show that the proposed methodology not only can achieve lower area than other similar tools, but that it achieves better testability compared to available testability enhancement tools such as tstfx. Specifically for ISCAS-85 benchmark circuits, it was observed that EX-OR gate-based transformations successfully contributed toward generating smaller circuits compared to other state-of-the-art logic optimization tools
Origin of life in a digital microcosm
While all organisms on Earth descend from a common ancestor, there is no
consensus on whether the origin of this ancestral self-replicator was a one-off
event or whether it was only the final survivor of multiple origins. Here we
use the digital evolution system Avida to study the origin of self-replicating
computer programs. By using a computational system, we avoid many of the
uncertainties inherent in any biochemical system of self-replicators (while
running the risk of ignoring a fundamental aspect of biochemistry). We
generated the exhaustive set of minimal-genome self-replicators and analyzed
the network structure of this fitness landscape. We further examined the
evolvability of these self-replicators and found that the evolvability of a
self-replicator is dependent on its genomic architecture. We studied the
differential ability of replicators to take over the population when competed
against each other (akin to a primordial-soup model of biogenesis) and found
that the probability of a self-replicator out-competing the others is not
uniform. Instead, progenitor (most-recent common ancestor) genotypes are
clustered in a small region of the replicator space. Our results demonstrate
how computational systems can be used as test systems for hypotheses concerning
the origin of life.Comment: 20 pages, 7 figures. To appear in special issue of Philosophical
Transactions of the Royal Society A: Re-Conceptualizing the Origins of Life
from a Physical Sciences Perspectiv
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