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.

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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