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Theoretical physicists working at a blackboard collaboration pod in the Beecroft building.
Credit: Jack Hobhouse

Ard Louis

Professor of Theoretical Physics

Research theme

  • Biological physics

Sub department

  • Rudolf Peierls Centre for Theoretical Physics

Research groups

  • Condensed Matter Theory
ard.louis@physics.ox.ac.uk
Louis Research Group members
Louis Research Group
  • About
  • Research
  • Publications on arXiv/bioRxiv
  • Publications

Coarse-grained modeling of DNA–RNA hybrids

Journal of Chemical Physics American Institute of Physics 160:11 (2024) 115101

Authors:

Eryk Ratajczyk, Petr Sulc, Andrew Turberfield, Jonathan Doye, Ard A Louis

Abstract:

We introduce oxNA, a new model for the simulation of DNA–RNA hybrids that is based on two previously developed coarse-grained models—oxDNA and oxRNA. The model naturally reproduces the physical properties of hybrid duplexes, including their structure, persistence length, and force-extension characteristics. By parameterizing the DNA–RNA hydrogen bonding interaction, we fit the model’s thermodynamic properties to experimental data using both average-sequence and sequence-dependent parameters. To demonstrate the model’s applicability, we provide three examples of its use—calculating the free energy profiles of hybrid strand displacement reactions, studying the resolution of a short R-loop, and simulating RNA-scaffolded wireframe origami.
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Exploring simplicity bias in 1D dynamical systems

(2024)

Authors:

Kamaludin Dingle, Mohammad Alaskandarani, Boumediene Hamzi, Ard A Louis
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Coarse-grained modelling of DNA-RNA hybrids

arXiv (2023) 1-15

Authors:

Eryk J Ratajczyk, Petr Šulc, Andrew J Turberfield, Jonathan PK Doye, Adriaan A Louis

Abstract:

We introduce oxNA, a new model for the simulation of DNA-RNA hybrids which is based on two previously developed coarse-grained models—oxDNA and oxRNA. The model naturally reproduces the physical properties of hybrid duplexes including their structure, persistence length and force-extension characteristics. By parameterising the DNA-RNA hydrogen bonding interaction we fit the model's thermodynamic properties to experimental data using both average-sequence and sequence-dependent parameters. To demonstrate the model's applicability we provide three examples of its use—calculating the free energy profiles of hybrid strand displacement reactions, studying the resolution of a short R-loop and simulating RNA-scaffolded wireframe origami.
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Maximum mutational robustness in genotype-phenotype maps follows a self-similar blancmange-like curve

Journal of the Royal Society Interface Royal Society 20:204 (2023) 20230169

Authors:

Vaibhav Mohanty, Sam F Greenbury, Tasmin Sarkany, Shyam Narayanan, Kamaludin Dingle, Sebastian E Ahnert, Ard A Louis

Abstract:

Phenotype robustness, defined as the average mutational robustness of all the genotypes that map to a given phenotype, plays a key role in facilitating neutral exploration of novel phenotypic variation by an evolving population. By applying results from coding theory, we prove that the maximum phenotype robustness occurs when genotypes are organized as bricklayer's graphs, so-called because they resemble the way in which a bricklayer would fill in a Hamming graph. The value of the maximal robustness is given by a fractal continuous everywhere but differentiable nowhere sums-of-digits function from number theory. Interestingly, genotype-phenotype maps for RNA secondary structure and the hydrophobic-polar (HP) model for protein folding can exhibit phenotype robustness that exactly attains this upper bound. By exploiting properties of the sums-of-digits function, we prove a lower bound on the deviation of the maximum robustness of phenotypes with multiple neutral components from the bricklayer's graph bound, and show that RNA secondary structure phenotypes obey this bound. Finally, we show how robustness changes when phenotypes are coarse-grained and derive a formula and associated bounds for the transition probabilities between such phenotypes.
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Do deep neural networks have an inbuilt Occam's razor?

(2023)

Authors:

Chris Mingard, Henry Rees, Guillermo Valle-Pérez, Ard A Louis
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