27,258 research outputs found
Extended master equation models for molecular communication networks
We consider molecular communication networks consisting of transmitters and
receivers distributed in a fluidic medium. In such networks, a transmitter
sends one or more signalling molecules, which are diffused over the medium, to
the receiver to realise the communication. In order to be able to engineer
synthetic molecular communication networks, mathematical models for these
networks are required. This paper proposes a new stochastic model for molecular
communication networks called reaction-diffusion master equation with exogenous
input (RDMEX). The key idea behind RDMEX is to model the transmitters as time
series of signalling molecule counts, while diffusion in the medium and
chemical reactions at the receivers are modelled as Markov processes using
master equation. An advantage of RDMEX is that it can readily be used to model
molecular communication networks with multiple transmitters and receivers. For
the case where the reaction kinetics at the receivers is linear, we show how
RDMEX can be used to determine the mean and covariance of the receiver output
signals, and derive closed-form expressions for the mean receiver output signal
of the RDMEX model. These closed-form expressions reveal that the output signal
of a receiver can be affected by the presence of other receivers. Numerical
examples are provided to demonstrate the properties of the model.Comment: IEEE Transactions on Nanobioscience, 201
Mapping energy transport networks in proteins
The response of proteins to chemical reactions or impulsive excitation that
occurs within the molecule has fascinated chemists for decades. In recent years
ultrafast X-ray studies have provided ever more detailed information about the
evolution of protein structural change following ligand photolysis, and
time-resolved IR and Raman techniques, e.g., have provided detailed pictures of
the nature and rate of energy transport in peptides and proteins, including
recent advances in identifying transport through individual amino acids of
several heme proteins. Computational tools to locate energy transport pathways
in proteins have also been advancing. Energy transport pathways in proteins
have since some time been identified by molecular dynamics (MD) simulations,
and more recent efforts have focused on the development of coarse graining
approaches, some of which have exploited analogies to thermal transport in
other molecular materials. With the identification of pathways in proteins and
protein complexes, network analysis has been applied to locate residues that
control protein dynamics and possibly allostery, where chemical reactions at
one binding site mediate reactions at distance sites of the protein. In this
chapter we review approaches for locating computationally energy transport
networks in proteins. We present background into energy and thermal transport
in condensed phase and macromolecules that underlies the approaches we discuss
before turning to a description of the approaches themselves. We also
illustrate the application of the computational methods for locating energy
transport networks and simulating energy dynamics in proteins with several
examples
Impact of receiver reaction mechanisms on the performance of molecular communication networks
In a molecular communication network, transmitters and receivers communicate
by using signalling molecules. At the receivers, the signalling molecules
react, via a chain of chemical reactions, to produce output molecules. The
counts of output molecules over time is considered to be the output signal of
the receiver. This output signal is used to detect the presence of signalling
molecules at the receiver. The output signal is noisy due to the stochastic
nature of diffusion and chemical reactions. The aim of this paper is to
characterise the properties of the output signals for two types of receivers,
which are based on two different types of reaction mechanisms. We derive
analytical expressions for the mean, variance and frequency properties of these
two types of receivers. These expressions allow us to study the properties of
these two types of receivers. In addition, our model allows us to study the
effect of the diffusibility of the receiver membrane on the performance of the
receivers
Molecular communication networks with general molecular circuit receivers
In a molecular communication network, transmitters may encode information in
concentration or frequency of signalling molecules. When the signalling
molecules reach the receivers, they react, via a set of chemical reactions or a
molecular circuit, to produce output molecules. The counts of output molecules
over time is the output signal of the receiver. The aim of this paper is to
investigate the impact of different reaction types on the information
transmission capacity of molecular communication networks. We realise this aim
by using a general molecular circuit model. We derive general expressions of
mean receiver output, and signal and noise spectra. We use these expressions to
investigate the information transmission capacities of a number of molecular
circuits
Formal executable descriptions of biological systems
The similarities between systems of living entities and systems of concurrent processes may support biological experiments in silico. Process calculi offer a formal framework to describe biological systems, as well as to analyse their behaviour, both from a qualitative and a quantitative point of view. A couple of little examples help us in showing how this can be done. We mainly focus our attention on the qualitative and quantitative aspects of the considered biological systems, and briefly illustrate which kinds of analysis are possible. We use a known stochastic calculus for the first example. We then present some statistics collected by repeatedly running the specification, that turn out to agree with those obtained by experiments in vivo. Our second example motivates a richer calculus. Its stochastic extension requires a non trivial machinery to faithfully reflect the real dynamic behaviour of biological systems
On the master equation approach to diffusive grain-surface chemistry: the H, O, CO system
We have used the master equation approach to study a moderately complex
network of diffusive reactions occurring on the surfaces of interstellar dust
particles. This network is meant to apply to dense clouds in which a large
portion of the gas-phase carbon has already been converted to carbon monoxide.
Hydrogen atoms, oxygen atoms, and CO molecules are allowed to accrete onto dust
particles and their chemistry is followed. The stable molecules produced are
oxygen, hydrogen, water, carbon dioxide (CO2), formaldehyde (H2CO), and
methanol (CH3OH). The surface abundances calculated via the master equation
approach are in good agreement with those obtained via a Monte Carlo method but
can differ considerably from those obtained with standard rate equations.Comment: 13 pages, 5 figure
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