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Found 7 papers, 5 papers with code
Optimal control of ribosome population for gene expression under periodic nutrient intake
Using biophysical parameter values, we find that optimal control solutions lead to both control mechanisms and the ribosome population switching between periods of feeding and fasting, suggesting that the intense regulation of ribosome population observed in experiments allows to maximize and maintain protein production.
Visualizing DNA reaction trajectories with deep graph embedding approaches
Synthetic biologists and molecular programmers design novel nucleic acid reactions, with many potential applications.
ViDa: Visualizing DNA hybridization trajectories with biophysics-informed deep graph embeddings
Visualization tools can help synthetic biologists and molecular programmers understand the complex reactive pathways of nucleic acid reactions, which can be designed for many potential applications and can be modelled using a continuous-time Markov chain (CTMC).
EMPOT: partial alignment of density maps and rigid body fitting using unbalanced Gromov-Wasserstein divergence
Aligning EM density maps and fitting atomic models are essential steps in single particle cryogenic electron microscopy (cryo-EM), with recent methods leveraging various algorithms and machine learning tools.
Quantifying Extrinsic Curvature in Neural Manifolds
The neural manifold hypothesis postulates that the activity of a neural population forms a low-dimensional manifold whose structure reflects that of the encoded task variables.
Testing geometric representation hypotheses from simulated place cell recordings
Hippocampal place cells can encode spatial locations of an animal in physical or task-relevant spaces.
Defining an action of SO(d)-rotations on images generated by projections of d-dimensional objects: Applications to pose inference with Geometric VAEs
Recent advances in variational autoencoders (VAEs) have enabled learning latent manifolds as compact Lie groups, such as $SO(d)$.
