Daniel Cutting
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View article: Computational design of therapeutic antibodies with improved developability: efficient traversal of binder landscapes and rescue of escape mutations
Computational design of therapeutic antibodies with improved developability: efficient traversal of binder landscapes and rescue of escape mutations Open
Developing therapeutic antibodies is a challenging endeavor, often requiring large-scale screening to produce initial binders, that still often require optimization for developability. We present a computational pipeline for the discovery …
View article: Computational design of developable therapeutic antibodies: efficient traversal of binder landscapes and rescue of escape mutations
Computational design of developable therapeutic antibodies: efficient traversal of binder landscapes and rescue of escape mutations Open
Developing therapeutic antibodies is a challenging endeavour, often requiring large-scale screening to produce initial binders, that still often require optimisation for developability. We present a computational pipeline for the discovery…
View article: ABodyBuilder3: improved and scalable antibody structure predictions
ABodyBuilder3: improved and scalable antibody structure predictions Open
Summary In this article, we introduce ABodyBuilder3, an improved and scalable antibody structure prediction model based on ABodyBuilder2. We achieve a new state-of-the-art accuracy in the modelling of CDR loops by leveraging language model…
View article: Towards the accurate modelling of antibody−antigen complexes from sequence using machine learning and information-driven docking
Towards the accurate modelling of antibody−antigen complexes from sequence using machine learning and information-driven docking Open
Motivation Antibody−antigen complex modelling is an important step in computational workflows for therapeutic antibody design. While experimentally determined structures of both antibody and the cognate antigen are often not available, rec…
View article: ABodyBuilder3: Improved and scalable antibody structure predictions
ABodyBuilder3: Improved and scalable antibody structure predictions Open
Accurate prediction of antibody structure is a central task in the design and development of monoclonal antibodies, notably to understand both their developability and their binding properties. In this article, we introduce ABodyBuilder3, …
View article: De novo antibody design with SE(3) diffusion
De novo antibody design with SE(3) diffusion Open
We introduce IgDiff, an antibody variable domain diffusion model based on a general protein backbone diffusion framework which was extended to handle multiple chains. Assessing the designability and novelty of the structures generated with…
View article: Towards the accurate modelling of antibody-antigen complexes from sequence using machine learning and information-driven docking
Towards the accurate modelling of antibody-antigen complexes from sequence using machine learning and information-driven docking Open
Antibody-antigen complex modelling is an important step in computational workflows for therapeutic antibody design. While experimentally determined structures of both antibody and the cognate antigen are often not available, recent advance…
View article: Inverse folding for antibody sequence design using deep learning
Inverse folding for antibody sequence design using deep learning Open
We consider the problem of antibody sequence design given 3D structural information. Building on previous work, we propose a fine-tuned inverse folding model that is specifically optimised for antibody structures and outperforms generic pr…
View article: Inverse folding for antibody sequence design using deep learning
Inverse folding for antibody sequence design using deep learning Open
Model weights of the AbMPNN model (arXiv:2310.19513) presented at the 2023 ICML Workshop on Computational Biology, and csv files with the split between train, test and validation across the SAbDab and ImmuneBuilder datasets. This model is …
View article: Inverse folding for antibody sequence design using deep learning
Inverse folding for antibody sequence design using deep learning Open
Model weights of the AbMPNN model (arXiv:2310.19513) presented at the 2023 ICML Workshop on Computational Biology, and csv files with the split between train, test and validation across the SAbDab and ImmuneBuilder datasets. This model is …
View article: Cosmology with the Laser Interferometer Space Antenna
Cosmology with the Laser Interferometer Space Antenna Open
The Laser Interferometer Space Antenna (LISA) has two scientific objectives of cosmological focus: to probe the expansion rate of the universe, and to understand stochastic gravitational-wave backgrounds and their implications for early un…
View article: Generation of gravitational waves from freely decaying turbulence
Generation of gravitational waves from freely decaying turbulence Open
We study the stochastic gravitational wave background (SGWB) produced by freely decaying vortical turbulence in the early Universe. We thoroughly investigate the time correlation of the velocity field, and hence of the anisotropic stresses…
View article: Machine learning a manifold
Machine learning a manifold Open
We propose a simple method to identify a continuous Lie algebra symmetry in a dataset through regression by an artificial neural network. Our proposal takes advantage of the $ \mathcal{O}(ε^2)$ scaling of the output variable under infinite…
View article: Droplet collapse during strongly supercooled transitions
Droplet collapse during strongly supercooled transitions Open
We simulate the decay of isolated, spherically symmetric droplets in a cosmological phase transition. It has long been posited that such heated droplets of the metastable state could form, and they have recently been observed in 3D multi-b…
View article: Gravitational waves from vacuum first-order phase transitions. II. From thin to thick walls
Gravitational waves from vacuum first-order phase transitions. II. From thin to thick walls Open
In a vacuum first-order phase transition, gravitational waves are generated from collision of bubbles of the true vacuum. The spectrum from such collisions takes the form of a broken power law. We consider a toy model for such a phase tran…
View article: Simulations of early universe phase transitions and gravitational waves
Simulations of early universe phase transitions and gravitational waves Open
Upcoming space based gravitational wave observatories like the Laser Interferometer Space Antenna (LISA) will provide a new window into early universe physics. While the results from ground-based detectors have largely concerned astrophysi…
View article: EuCAPT White Paper: Opportunities and Challenges for Theoretical Astroparticle Physics in the Next Decade
EuCAPT White Paper: Opportunities and Challenges for Theoretical Astroparticle Physics in the Next Decade Open
Astroparticle physics is undergoing a profound transformation, due to a series of extraordinary new results, such as the discovery of high-energy cosmic neutrinos with IceCube, the direct detection of gravitational waves with LIGO and Virg…
View article: Vorticity, Kinetic Energy, and Suppressed Gravitational-Wave Production in Strong First-Order Phase Transitions
Vorticity, Kinetic Energy, and Suppressed Gravitational-Wave Production in Strong First-Order Phase Transitions Open
We have performed the first three-dimensional simulations of strong first-order thermal phase transitions in the early universe. For deflagrations, we find that the rotational component of the fluid velocity increases as the transition str…
View article: Gravitational waves from vacuum first-order phase transitions: From the envelope to the lattice
Gravitational waves from vacuum first-order phase transitions: From the envelope to the lattice Open
Movie based on Figure 2 of the paper Gravitational waves from vacuum first-order phase transitions: from the envelope to the lattice [arXiv:1802.05712]. This movie originally appeared as Supplemental Material associated with the paper. Cap…