The framework predicts how proteins will function with several interacting mutations and finds combinations that work well together.
Korea University researchers have developed a machine-learning framework that predicts solar cell efficiency from wafer quality, enabling early wafer screening and optimized production paths. Using ...
Researchers used 16S rRNA sequencing and machine learning to identify gut microbiome patterns associated with insulin ...
3don MSN
Machine learning model predicts serious transplant complications months before symptoms appear
A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and microfluidics to nanomaterial testing, thanks to their compact size and ...
Insulin resistance - when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels - ...
Phishing websites remain a persistent cybersecurity threat, exploiting users by imitating trusted online services. New ...
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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