Explores the evolution and function of protein-repair machineries, emphasizing the role of ATP-fueled unfolding machines in preventing protein aggregation and promoting proper folding.
Explores predicting protein structure from sequence data using maximum entropy modeling and discusses recent advancements in protein structure prediction.
Explores protein folding, amino acids, RNA translation, and attractive forces, emphasizing the importance of native state conformation and compact structures.
Explores a unified framework for understanding and evaluating generative sequence models of DNA/RNA or Protein, covering topics like coevolution, conservation, and different models such as GREMLIN and BERT.
Explores translation, mutations, ribosome function, protein folding, and degradation processes, emphasizing the genetic code's role in protein synthesis.
Explores trajectory forecasting in autonomous vehicles, focusing on deep learning models for predicting human trajectories in socially-aware transportation scenarios.
