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

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

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.

"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 ...

TensorFlow is an open source machine learning framework developed by Google, designed to build and train AI models for a wide range of applications. The tool is widely used in industries such as ...

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

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

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 ...

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could ...

In this project, the student will work on probabilistic modelling and machine-learning techniques to advance the current description of nuclear reactions in specific energy regimes of astrophysical ...