The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.

Engineered enzymes are poised to have transformative impacts across applications in energy, materials, biotechnology, and medicine. Recently, machine learning has emerged as a useful tool for enzyme ...

More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...

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

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 ...

AI, Machine Learning & Robotics research at Drexel University's College of Computing & Informatics (CCI) explores algorithms, mathematics, and applications of artificial intelligence (AI) through ...

Mechanical engineering has traditionally relied on physics, mathematics, and empirical knowledge to design and optimize systems. Machine learning (ML) introduces powerful tools that can complement ...

Fabs are beginning to deploy machine learning models to drill deep into complex processes, leveraging both vast compute power and significant advances in ML. All of this is necessary as dimensions ...

Since the first FEA solver, Nastran, was developed for NASA in the 1960s, the simulation software industry has contended with a number of hurdles. For one, while the software (FEA, CFD, CEM) is ...