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LD Motif Finder locates ancient hidden protein patterns
LD Motif Finder locates ancient hidden protein patterns
LD Motif Finder locates ancient hidden protein patterns
A machine learning method has identified highly elusive amino acid sequences involved in cell morphogenesis and adhesion and in diseases like cancer.
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KAUST research conference: Digital Heatlh 2020
KAUST research conference: Digital Heatlh 2020
KAUST research conference: Digital Heatlh 2020
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AI reveals nature of RNA-protein interactions
AI reveals nature of RNA-protein interactions
A new computational tool developed by KAUST scientists uses artificial intelligence (AI) to infer the RNA-binding properties of proteins.
The software, called NucleicNet, outperforms other algorithmic models of its kind and provides additional biological insights that could aid in drug design and development.
In collaboration with researchers in China and the United States, Lam, Li and Gao validated their algorithm on a diverse set of RNA-binding proteins, including proteins implicated in gum cancer and amyotrophic lateral sclerosis, to show that the interactions deduced by NucleicNet closely matched those revealed by experimental techniques. They reported the findings in Nature Communications.
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