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 20100 possible variants—more combinations than atoms in the observable universe.
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New agent framework matches human-engineered AI systems — and adds zero inference cost to deploy
A new group-evolving agent framework from UC Santa Barbara matches human-engineered AI systems on SWE-bench — and adds zero ...
Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...
A Purdue University digital forestry team has created a computational tool to obtain and analyze urban tree inventories on ...
A team of UCSF researchers successfully tested several mainstream AI agents for the ability to analyze big data on women's ...
Abstract: Accurate estimation of State-of-Charge (SoC) and core temperature is fundamental to optimizing the performance, safety, and longevity of Lithium-Ion Batteries (LiBs), particularly in ...
Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
The Venice International Film Festival just witnessed one of its most powerful moments this year, and it had nothing to do with red carpets or photo ops. Instead, Dwayne Johnson uncontrollably sobbed ...
ABSTRACT: This study presents a comprehensive and interpretable machine learning pipeline for predicting treatment resistance in psychiatric disorders using synthetically generated, multimodal data.
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