Automated Assignment of Backbone NMR Data using Artificial Intelligence
This addresses the problem of efficiently determining protein structures for understanding function and disease, but it appears incremental as it applies existing AI methods to a known bottleneck in NMR analysis.
The researchers tackled the challenge of automating backbone protein NMR data analysis by designing an algorithm using AI strategies like greedy and A* search, but no concrete results or numbers are provided.
Nuclear magnetic resonance (NMR) spectroscopy is a powerful method for the investigation of three-dimensional structures of biological molecules such as proteins. Determining a protein structure is essential for understanding its function and alterations in function which lead to disease. One of the major challenges of the post-genomic era is to obtain structural and functional information on the many unknown proteins encoded by thousands of newly identified genes. The goal of this research is to design an algorithm capable of automating the analysis of backbone protein NMR data by implementing AI strategies such as greedy and A* search.