Publications by authors named "Andreas Loukas"

Article Synopsis
  • De novo protein design aims to create new proteins that evolution hasn't explored, with challenges in developing structural templates to guide the design process.* -
  • Researchers introduced "Genesis," a convolutional variational autoencoder, which effectively learns protein structure patterns and collaborates with trRosetta to design sequences for various protein folds.* -
  • The team demonstrated Genesis's ability to replicate native-like structural features in both known and novel protein folds, showcasing its potential for rapid protein design while addressing designability issues effectively.*
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Proteins are typically represented by discrete atomic coordinates providing an accessible framework to describe different conformations. However, in some fields proteins are more accurately represented as near-continuous surfaces, as these are imprinted with geometric (shape) and chemical (electrostatics) features of the underlying protein structure. Protein surfaces are dependent on their chemical composition and, ultimately determine protein function, acting as the interface that engages in interactions with other molecules.

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This paper considers regression tasks involving high-dimensional multivariate processes whose structure is dependent on some known graph topology. We put forth a new definition of time-vertex wide-sense stationarity, or for short, that goes beyond product graphs. Joint stationarity helps by reducing the estimation variance and recovery complexity.

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