Reading List

Mostly for internal reference - a list of papers we've discussed in our fortnightly literature meetings. Highlights may be featured as blog posts.


Computing properties of stable configurations of thermodynamic binding networks
This paper describes a method to calculate all the possible thermodynmaic tradeoffs (focused in enthalpy and entropy) in DNA chemical reaction networks allowing the prediction of all the possible pairings given at a domain level, which can result on the prediction and estimation of the rates of undesired leak reaction rates. Although very useful in principle, this work is only a first limited step since it only predicts and calculates at the abstracted domain level.

Cell cycle switch computes approximate majority
The paper shows that a biologically plausible circuit, namely a cell-cycle switch, simulates the approximate majority algorithm. Deterministic (ODEs), stochastic (gillespie simulations) and probabilistic analyses are performed to compare the performance of the two circuits. Though the performance of the cycle-cycle switch is slightly sub-optimal compared to the circuit computing the approximate majority algorithm, the introduction of a feedback loop called the "greatwall kinase" corrects this effect, by improving both the speed and conversion to majority.

Synchrony and pattern formation of coupled genetic oscillators on a chip of artificial cells
In the paper, the authors produce a silicon microfluidics-chip with several compartments interconnected by a central channel. Each of these compartments are functionalized with several DNA sequences that encodes proteins for an oscillatory network and a reporter (GFP). The oscillatory behaviour is produced by flowing through the central channel an E.coli transcription-extract with a transcription activator and repressor that reach through diffusion to the functionalized compartments.

By altering the ratio of the different genes' promoters, the researchers are able to change the oscillation frequency of the cells. In addition, the connection of the compartments between them with the central channel produce a synchronization mediated only by diffusion. While the cells produce random oscillations without communication between them, when communicated they acquire the same frequency, determined by the slowest one.  This synchronization strength is easily controlled by varying the geometry or breaking the symmetry of the flow.

This microfluidic approach is a useful bottom-up approach for genetic-oscillator interactions, which allows to precisely control the experimental parameters and observe a wide variety of oscillatory behaviours.

Mapping of uncertainty relations between continuous and discrete time
This paper shows a relationship between the thermodynamic uncertainty relation for discrete and continuous time Markov chains in the long time limit. The variance of a current is always greater in the continuous time case because of the uncertainty in the time of the transitions. They use this relationship to transform a bound called the Proesmans-Van den Broeck bound for discrete time process to one for continuous time processes and show that is tighter than the Barato-Gingrich bound.

Modular probes for enriching and detecting complex nucleic acid sequences
The authors introduce a design for a DNA "probe" intended to detect the presence of complementary sequences in solution. This particular design is modular, allowing the authors to build longer probes than were previously possible, and includes small subsections in which the probe is not specific to a particular target sequence (at the joins between modules). This could be viewed as an advantage or a disadvantage, depending on context. 

Mixed analytical-stochastic simulation method for the recovery of a Brownian gradient source from probability fluxes to small windows
In this paper the authors show how a cell can detect the position of a source of Brownian particles using the particle flux into absorbing patches on its surface. They also demonstrate a simulation method that uses Green’s functions for efficient simulation of diffusion in some regions and explicit integration of Brownian motion via Euler’s method in others.

Robust Weak Chimeras in Oscillator Networks with Delayed Linear
and Quadratic Interactions

Chimera states are complex spatio-temporal patterns in which domains of synchronous and asynchronous dynamics coexist in coupled systems of oscillators. In this paper, the authors show the production of robust chimeras in networks of two populations of two oscillators. They obtain this with a weak coupling function with two sinusoidal terms: a linear and quadratic time-delayed interactions.

They test the approach numerically with the Brusselator model and experimentally with an electrochemical  oscillatory reaction. The results show how complex collective dynamics in phase models translate into limit cycle oscillator networks in real biological processes.

Maximal aggregation of polynomial dynamical systems
The paper give an algorithm for the reduction of ordinary differential equations up to an equivalence relation over it’s variables. The algorithm preserves structure and variables of interest. Applications of this algorithm are presented in the context of regulatory networks, evolutionary game theory and molecular biology.

Post CMOS Computing Beyond Si: DNA Computing as Future Alternative. (
This paper is a brief review of the DNA computing field in which the different algorithmic operations that can be performed with DNA are described. The original approaches in the field (the Adelman-Lipton model and the stickers model) are also described in detail. This work also offers a very brief summary of the kind of problems that have been tackled, as well as their problems in implementing arithmetic operations. Worthy as a basis for introducing students to the field

Constructor Theory of Thermodynamics
Oxford-based researchers are endeavouring to re-frame fundamental ideas of physics in terms of whether it is theoretically possible to build devices (or "constructors") that can be guaranteed to achieve a certain "task". This paper seeks to do this for the laws of thermodynamics. In particular, much of the effort is spent trying to develop a rigorous and  general definition of work and heat.

Sufficient physical conditions for self-replication
The authors introduce a simple model that can exhibit auto-catalytic cycles that eventually lead to exponential growth of finite-size clusters from a pool of monomers (for this it is crucial that the maximum cluster size is capped). They observe that this exponential growth is favoured when autocatalytic cycles involve reactions that are highly specific - ie., components involved in the cycle overwhelmingly undergo reactions in the cycle, rather than competing alternative reactions.

A tensegrity driven DNA nanopore.
This paper describes the design of a DNA nanopore the mimics the function of those at biological membrane.  It consists in 6 B-DNA helixes forming the main structure of the pore, which is modified with hydrophobic domains that allow its insertion in lipid bilayers and block the pore lumen when closed.  The opening mechanism of the pore involves a ssDNA sequence on the top of the pore that in presence of its complementary strand forms a stiff double helix that with its tension forces changes in the structure of the pore and consequently its opening.

Conservation Laws shape Dissipation
In this paper the authors describe a general formulation of stochastic thermodynamics with multiple reservoirs. They show how conserved quantities cause the forces from the reservoirs to be absorbed into the potentials of the states of the system in the local detailed balance equation. They also show how to separate the entropy production into a part that depends on how the potentials are changed over time, a part that depends on the difference between the potential of the initial and final state and a part that depends on the fundamental forces.

Iterated function systems for DNA replication
Here, Gaspard generalises his previous solutions for solving the mechanics of the creation of polymer copies by no longer allowing the simplification that all matches can be considered "correct" or "incorrect". Instead, for DNA, he considers the dynamics of all 16 possible base pair combinations. This extra heterogeneity leads to imbalances in concentration between nucleotides at different points in the chain.  This, in turn, leads to regions of "anomalous drift" where the growth of the polymer is sub linear.

Exponential growth and selection in self-replicating materials from DNA origami rafts
The authors have successfully created a system in which DNA origami rafts form dimers that co-operatively catalyse their own formation in a specific manner,  leading to exponential growth of specific dimer pairs. This process involves a complex external protocol involving cycling of temperatures and periodic UV exposure.

Thermodynamically Consistent Coarse Graining of Biocatalysts
The paper provides a mechanism to understand properties of the reaction network at the coarse grained level. In particular, physical quantities like flux, reaction stoichiometry and force relations are provided at the coarse-grained level of the reaction network. The entire mechanism is ensured to be thermodynamically consistent. Examples are illustrated using a single catalyst that reacts with two substrates to form a product, and a representative model of active membrane protein transport.

A cargo-shorting DNA robot.
The most recent work from the Winfree and Qian groups describes the construction of a modular DNA walker capable of carrying  DNA cargoes. Through a random walk process the aforementioned cargoes are selectively transported to a specific zone of a DNA origami.

Associative Pattern Recognition Through Macro-molecular Self-Assembly
Multifarious assembly mixtures: Systems allowing  retrieval of diverse stored structures
The authors ask how many separate self-assembly targets can be programmed into the interactions between a mixture of monomers, assuming that monomers must be re-used (in different patterns) in each fully-assembled structure. They explore the conditions under which a single well-formed assembly can be triggered by seeding a small part of it, and then relate this process to the idea of retrieving memories. 

This paper considers chemical reaction networks forced out of equilibrium by a generalised chemical driving force (which is justified by appealing to implicit degrees of freedom). They watch the system evolve with time and observe a bi-modal distribution of outcomes in which, while most of the possible networks are in equilibrium or lowly dissipative, a small fraction of the configurations evolves to become much more highly dissipative and finely tuned to the work source of the environment than the rest. These finely-tuned setups occur much more often than would be expected by chance. 

This paper analysis a system which involves polymer creation through processes of random ligation and auto-catalysis. It finds that, in a regime dominated by auto-catalysis, repetitive, highly patterned structures are by far the most common. It suggests two possible explanations, one short term and far from equilibrium, and one in the steady state. Both explanations hinge on the idea that longer polymers can absorb more different kinds of material when creating themselves through auto-catalysis, and for a given amount of input material, and regular polymers can form longer chains than irregular ones when creating themselves by random ligation.

Marzen and Crutchfield present a theoretical treatment of conditionally Markovian systems Y driven by hidden-Markovian environments X. They are able to derive expressions for certain  information-theoretic and thermodynamic quantities related to the combined process. They use these expressions to study information and dissipation in the sensing of ligands that bind cooperatively to a sensor.  

The paper gives a sufficient condition for a chemical reaction network to have an extinction event. More explicitly, they introduce the notion of a dominated expanded reaction network and provide a set of conditions on this network that do not need to be satisfied for an extinction event to occur. Solving such a system of equalities/inequalities makes the question of finding an extinction event in the reaction network amenable to algorithmic approaches.

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.

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.

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.

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