The framework predicts how proteins will function with several interacting mutations and finds combinations that work well together.

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 ...

A new artificial intelligence framework developed at Cornell can accurately predict the performance of battery electrolytes ...

"We believe that our framework combines best practices in the field and provides a conceptual blueprint on how to work with and analyze experimental catalyst data, which should prove useful to future ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 possible variants—more combinations than atoms in the observable universe.

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

High-entropy alloys are promising advanced materials for demanding applications, but discovering useful compositions is difficult and expensive due to the vast number of possible element combinations.

Neuroblastoma is the most common solid tumor in infants and accounts for nearly 15% of all pediatric cancer-related deaths. Despite decades of progress in surgery, chemotherapy, and stem cell ...

For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...