3 accepted papers
Accurately predicting experimentally-realizable $3\textrm{D}$ molecular crystal structures from their $2\textrm{D}$ chemical graphs is a long-standing open challenge in computational chemistry called $\textit{crystal structure prediction}$ (CSP). Efficiently solving this problem has implications ran…
Protein fitness optimization involves finding a protein sequence that maximizes desired quantitative properties in a combinatorially large design space of possible sequences. Recent advances in steering protein generative models (e.g., diffusion models and language models) with labeled data offer a…
Enzymes are important proteins that catalyze chemical reactions. In recent years, machine learning methods have emerged to predict enzyme function from sequence; however, there are no standardized benchmarks to evaluate these methods. We introduce CARE, a benchmark and dataset suite for the Classif…