In a new study published in Nature titled, “Custom CRISPR-Cas9 PAM variants via scalable engineering and machine learning,” researchers from Massachusetts General Hospital (MGH) and Harvard Medical ...

Machine learning (ML) is transforming protein structure prediction. Algorithms can predict 3D structures from amino acid sequences, surpassing slower, more expensive traditional methods. ML-based ...

An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin introduces a breakthrough in protein simulation. The study, published in the ...

The “ChatGPT moment” for biology proceeds to unfold as protein language models, or machine learning tools trained on large databases of protein sequences, work to decode the language of life with the ...

CGSchNet, a fast machine-learned model, simulates proteins with high accuracy, enabling drug discovery and protein engineering for cancer treatment. Operating significantly faster than traditional all ...

Scientists have used deep learning to design new proteins that bind to complexes involving other small molecules like hormones or drugs, opening up a world of possibilities in the computational design ...

A platform to engineer enzymes responsible for the formation of amide bonds as an effort toward developing biocatalysts for green chemistry. Amide bonds — a type of chemical bond formed between a ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

The 2024 Nobel Prize in chemistry recognized Demis Hassabis, John Jumper and David Baker for using machine learning to tackle ...

Ansys SimAI is a physics-agnostic and cloud-enabled computer-aided engineering tool that predicts performance of complex simulation scenarios. The game-changer? Engineers train their model and use it ...