**19/01/2017**

Stochastic Analysis of Retroactivity in Transcriptional Networks through Singular Perturbation

An analysis of the restroactive effect on transcription factor abundance due to its interaction (and subsequent sequestration) with a downstream transcription site.

Information theory, predictability, and the emergence of complex life

Construction and analysis of a simple model in which the cost of being complex can be compensated by an increased ability to predict the environment.

A DNA kinetics competition strategy of hybridization chain reaction for molecular information processing circuit construction

A molecular circuit that responds not just to the presence of multiple signals, but distinguishes between signals in different orders.

An analysis of the costs of generating periodic behaviour in simple stochastic systems.

Signal replication in a DNA nanostructure

Localised DNA strand displacement reactions for implementing logic in which a single signal can be branched into a multiple finite number of outputs.

Kinetics and thermodynamics of first-order Markov chain copolymerization

A technique for analyzing the growth of polymers with multiple different constituent monomers, in which monomer addition/removal rates depend upon the neighbouring monomers.

Online learning in a chemical perceptron

Implementing a simple neuron using molecular reactions.

Least mean squares implementation using molecules

Implementing a learning algorithm using chemical reactions.

Design of a hyperstable 60-subunit protein icosahedron

and

Accurate design of megadalton-scale two-component icosahedral protein complexes.

Icosahedral cages assembled from genetically modified proteins, with components produced and assembling in living E coli cells.

Effective dissipation: Breaking time-reversal symmetry in driven microscopic energy transmission

An analysis of when a simple device for driving a particle up a step is most dissipative.

Catalysis in reaction networks

Proof that in weakly reversible reaction networks that don't involve catalysis, it is impossible for the concentration of any subset of species to tend asymptotically to zero.

**02/02/2017**Signal replication in a DNA nanostructure

Localised DNA strand displacement reactions for implementing logic in which a single signal can be branched into a multiple finite number of outputs.

Kinetics and thermodynamics of first-order Markov chain copolymerization

A technique for analyzing the growth of polymers with multiple different constituent monomers, in which monomer addition/removal rates depend upon the neighbouring monomers.

Online learning in a chemical perceptron

Implementing a simple neuron using molecular reactions.

Least mean squares implementation using molecules

Implementing a learning algorithm using chemical reactions.

Design of a hyperstable 60-subunit protein icosahedron

and

Accurate design of megadalton-scale two-component icosahedral protein complexes.

Icosahedral cages assembled from genetically modified proteins, with components produced and assembling in living E coli cells.

**16/02/2017**Effective dissipation: Breaking time-reversal symmetry in driven microscopic energy transmission

An analysis of when a simple device for driving a particle up a step is most dissipative.

Catalysis in reaction networks

Proof that in weakly reversible reaction networks that don't involve catalysis, it is impossible for the concentration of any subset of species to tend asymptotically to zero.

# Towards a DNA Nanoprocessor: Reusable Tile-Integrated DNA Circuits

An implementation of DNA-based logic gates that can be incorporated into a small DNA tile.

An analysis of information exchange between multiple interacting systems.

An analysis of an experiment in which measurement and feedback allows photons from two competing beams to charge a capacitor (no charging occurs when photons are not measured). This paper discusses the case in which fluctuations of photon numbers in both beams are correlated, allowing more work extraction.

Mutual Information between Input and Output Trajectories of Biochemical Networks

Calculating the information passed by a signalling system. This work, by considering simple gaussian fluctuations, is able to analyse the information between entire trajectories, rather than just the instantaneous information.

Message Passing Inference with Chemical Reaction Networks

Certain types of probability distribution can be marginalised through an algorithm known as message passing. This paper discusses how to implement chemical reactions that achieve such a goal.

Computing exponentially faster: implementing a non-deterministic universal Turing machine using DNA

A proposal to implement an unconventional computing architecture in which the inherent stochasticity of molecular processes is employed to simultaneously explore many possible solutions to a problem.

Thermodynamic Uncertainty Relation for Biomolecular Processes

First in a series of papers that explore the connection between the entropy generation around a cycle of molecular states and the uncertainty in the number of cycles completed in a given time.

Regulation of DNA Strand Displacement Using an Allosteric DNA Toehold

A new mechanism for controlling of DNA strand displacement with regulator strands.

In vitro molecular machine learning algorithm via symmetric internal loops of DNA

Encoding a classification problem into DNA molecules.

Heterotic computing: past, present and future

A review of the possibilities of using computing architectures built from components that are not themselves Turing complete.

Solving Moment Hierarchies for Chemical Reaction Networks

The authors present an approach for calculating the relative values of factorial moments for stochastic Chemical Reaction Networks in the steady state. Factorial moments are quantities related to means and variances of chemical populations.

Universal bound on the efficiency of molecular motors

By applying the recently-derived thermodynamic uncertainty relation, the authors find a bound on the efficiency of molecular motors that depends purely on observible quantities like the average velocity and diffusion constant.

Minimum energetic cost to maintain a target nonequilibrium state

The authors discuss the minimum rate at which energy must be supplied to maintain a non-equilibrium steady state in a discreet state Markov chain. It is the rate at which the system relaxes back towards equilibrium in the absence of the control.

Large-scale design of robust genetic circuits with multiple inputs and outputs for mammalian cell

This paper features the development of a recombinased-based framework for gene circuits design for synthethic biology. It must be remarked that this framework allows incredibly robust designs with little need for optimization, reduction of transcriptional layers as well as real time reprogrammability using CRISPR-Cas9 systems.

Universal trade-off between power, efficiency and constancy in steady-state heat engines

Recent work has suggested that heat engines operating between two temperature reservoirs can approach the limiting Carnot efficiency at finite power. This work argues that doing so is associated with a growing variance in the output power from one point in time to another.

Biological timekeeping in the presence of stochasticity

An analysis of the time taken to reach a certain threshold concentration in some biological systems. This time is less variable if the threshold is compared to an integral of concentrations over time, rather than instantaneous concentrations.

Approximating first-passage time distributions via sequential Bayesian computation.

This paper argues that the problem of finding the first passage time of a stochastic process is equivalent to a sequential Bayesian inference problem. It then uses approximations to efficiently calculate the first passage time distribution.

A Molecular Circuit Regenerator to Implement Iterative Strand Displacement Operations

This works shows the design of a strand displacement gate that can be regenerated through the consumption of fuel molecules of DNA. The concept is extended to the implementation of two boolean gates using on this motif. It should be noted that enthalpic and entropic components of the reactions have different weights in each direction, and that the regeneration reactions must have different kinetic orders in order to allow proper activation.

Nanoscale rotary apparatus formed from tight-fitting 3D DNA components

Stepping operation of a rotary DNA origami device

Two papers that aim to mimic some of the most remarkable biomolecular machines - powered rotary motors. In the first paper, the construct a freely-rotating axle from DNA, but do not power its motion. In the second case, the authors are able to set the rotational angle of one piece of DNA with repect ot the other. However, the system does not possess a truly free axle and consistent motion in a specific direction is not possible.

The derivation of Markov processes without detailed balance

Markov chain models of stochastic processes without detailed balance implicitly contain external degrees of freedom that drive the system. This paper shows how to embed the Markov chain in a larger Markov chain that explicitly includes these degrees of freedom. This larger Markov chain allows detailed balance (it satisfies Kolmogorov’s criterion) but is out of equilibrium and the embedding is only accurate for short times compared to the relaxation time of the driving degrees of freedom.

**23/03/2017**Mutual Information between Input and Output Trajectories of Biochemical Networks

Calculating the information passed by a signalling system. This work, by considering simple gaussian fluctuations, is able to analyse the information between entire trajectories, rather than just the instantaneous information.

Message Passing Inference with Chemical Reaction Networks

Certain types of probability distribution can be marginalised through an algorithm known as message passing. This paper discusses how to implement chemical reactions that achieve such a goal.

Computing exponentially faster: implementing a non-deterministic universal Turing machine using DNA

A proposal to implement an unconventional computing architecture in which the inherent stochasticity of molecular processes is employed to simultaneously explore many possible solutions to a problem.

Thermodynamic Uncertainty Relation for Biomolecular Processes

First in a series of papers that explore the connection between the entropy generation around a cycle of molecular states and the uncertainty in the number of cycles completed in a given time.

**27/04/2017**Regulation of DNA Strand Displacement Using an Allosteric DNA Toehold

A new mechanism for controlling of DNA strand displacement with regulator strands.

**11/05/2017**In vitro molecular machine learning algorithm via symmetric internal loops of DNA

Encoding a classification problem into DNA molecules.

Heterotic computing: past, present and future

A review of the possibilities of using computing architectures built from components that are not themselves Turing complete.

Solving Moment Hierarchies for Chemical Reaction Networks

The authors present an approach for calculating the relative values of factorial moments for stochastic Chemical Reaction Networks in the steady state. Factorial moments are quantities related to means and variances of chemical populations.

Universal bound on the efficiency of molecular motors

By applying the recently-derived thermodynamic uncertainty relation, the authors find a bound on the efficiency of molecular motors that depends purely on observible quantities like the average velocity and diffusion constant.

**26/05/2017**Minimum energetic cost to maintain a target nonequilibrium state

The authors discuss the minimum rate at which energy must be supplied to maintain a non-equilibrium steady state in a discreet state Markov chain. It is the rate at which the system relaxes back towards equilibrium in the absence of the control.

Large-scale design of robust genetic circuits with multiple inputs and outputs for mammalian cell

This paper features the development of a recombinased-based framework for gene circuits design for synthethic biology. It must be remarked that this framework allows incredibly robust designs with little need for optimization, reduction of transcriptional layers as well as real time reprogrammability using CRISPR-Cas9 systems.

Universal trade-off between power, efficiency and constancy in steady-state heat engines

Recent work has suggested that heat engines operating between two temperature reservoirs can approach the limiting Carnot efficiency at finite power. This work argues that doing so is associated with a growing variance in the output power from one point in time to another.

Biological timekeeping in the presence of stochasticity

An analysis of the time taken to reach a certain threshold concentration in some biological systems. This time is less variable if the threshold is compared to an integral of concentrations over time, rather than instantaneous concentrations.

**12/06/2017**Approximating first-passage time distributions via sequential Bayesian computation.

This paper argues that the problem of finding the first passage time of a stochastic process is equivalent to a sequential Bayesian inference problem. It then uses approximations to efficiently calculate the first passage time distribution.

A Molecular Circuit Regenerator to Implement Iterative Strand Displacement Operations

This works shows the design of a strand displacement gate that can be regenerated through the consumption of fuel molecules of DNA. The concept is extended to the implementation of two boolean gates using on this motif. It should be noted that enthalpic and entropic components of the reactions have different weights in each direction, and that the regeneration reactions must have different kinetic orders in order to allow proper activation.

Nanoscale rotary apparatus formed from tight-fitting 3D DNA components

Stepping operation of a rotary DNA origami device

Two papers that aim to mimic some of the most remarkable biomolecular machines - powered rotary motors. In the first paper, the construct a freely-rotating axle from DNA, but do not power its motion. In the second case, the authors are able to set the rotational angle of one piece of DNA with repect ot the other. However, the system does not possess a truly free axle and consistent motion in a specific direction is not possible.

**03/07/2017**
The authors find a bound on the distribution of the infimum of entropy production in a trajectory of a stochastic process. This can be used to find a bound on the average maximum backwards detour of a molecular motor. They calculate other quantities such as the probability of a trajectory reaching a positive entropy production before reaching the same magnitude negative entropy production and the ratio of the probability distribution of the time to reach those two states.

The RNA world hypothesis suggests that early life used RNA as both an information carrier and as chemically active catalysts. In particular, an RNA-based RNAp could in principle allow for RNA-based copying of RNA. Whilst some RNA-based polymerases do exist in nature, they are not effective at polymerising long, arbitrary sequences. Here, the authors obtain an RNA-based RNAp that can do just that by several rounds of selective evolution. Note that the functioning of the RNAp is restricted to growing a copy sequence on a single-stranded template; persistent copies can only be produced by thermal cycling.

Leak reactions are one of the main problems affecting reliability and performance of programmable DNA reaction networks. In this paper a solution to this problem is proposed through the combined use of 3-way and 4-way branch migration reaction motifs. 4-way branch migration offers a higher free-energy barrier to the metastable initial conditions of the reaction network lowering the leak reaction rates by two orders of magnitude, while 3-way branch migration allows partial compensation of the speed trade-offs in the network

**24/07/2017**

A first major step towards a systematic predictor for DNA hybridisation rates. Based on a wealth of data, the authors use a combination of metrics that can be easily calculated from the sequences to predict hybridisation rates. The approach is largely phenomenological, and currently only applies to one strand length, but its a big step forward non the less.

In this paper, the authors discuss fluctuations in the ‘information flow’, which is part of the time derivative of the mutual information between two interacting stochastic systems. They show that when considering just one of the two coupled systems, the information flow must be added to the entropy production for a fluctuation theorem to hold. They apply this to a system of two interacting Brownian particles.

The paper makes a connection between stochastic and deterministic chemical reaction networks. In particular, it shows that for complex balanced networks, the Lyapunov function of the deterministic reaction network arises as a scaling limit of the non-equilibrium potential corresponding to the stationary distribution of it’s stochastic network. In addition, it extends this result to some birth-death processes which are not complex balanced, however does not prove results in a greater generality.

This paper sets up a simple system that trains a neural network the form of a rule for generating outputs. It takes an input drawn randomly from a set potential, and acts on it with a teacher rule and a student rule, giving two different outcomes. The two outputs are compared and the student rule is updated to give an output closer to the output given by the teacher rule. This paper states that the increase in mutual information between the teacher and student rules must be less than the free energy dissipated for the process of the student learning from the teacher.

This paper features the description of the development of an aptamer-based platform for the Influenza virus diagnosis. The aptamers obtained through artificial evolution in this work are characterized by their capability of binding to many influenza virus subtypes, making it more robust to variations on the virus due to mutations and recombination.

**07/08/2017**

The derivation of Markov processes without detailed balance

Markov chain models of stochastic processes without detailed balance implicitly contain external degrees of freedom that drive the system. This paper shows how to embed the Markov chain in a larger Markov chain that explicitly includes these degrees of freedom. This larger Markov chain allows detailed balance (it satisfies Kolmogorov’s criterion) but is out of equilibrium and the embedding is only accurate for short times compared to the relaxation time of the driving degrees of freedom.

In this paper, the authors demonstrate the ability to correlate the number of photons in an optical cavity with the state of a qbit, based on the fact that the interactions between the cavity change the energy gap of the qbit/resonant frequency of the cavity. This correlation allows for an excess of stimulated emission over absorption when the qbit is exposed to light at the natural frequency f the isolated qbit.

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