In recent years, machine learning and artificial intelligence has found unique applications in a plethora of fields and industries. Specifically, in organic chemistry, machine learning algorithms have been used to predict organic synthesis strategies based on previous patented data. Although the current available programs have shown over 90% accuracy on many common industrial reactions, they […]
A07-P: Using a Machine Learning Approach to Identify Potential Metallo-β-Lactamase Inhibitors
This project combines the fields of biochemistry and data science by applying a machine learning approach to the identification of potential metallo-β-lactamase (MBL) inhibitors. MBLs are enzymes expressed by antibiotic-resistant bacteria and are becoming more clinically prevalent, leading to an increasing number of severe cases of once easily-treatable infections. In recent years, there has been […]