Bacterial Interaction

Bacterial interactions, and more broadly, host-pathogen interactions, are being intensely studied to understand microbial community dynamics and infectious disease mechanisms. Current research leverages machine learning, particularly deep learning models and transfer learning approaches, to analyze large datasets of genomic and proteomic information, aiming to predict interactions and identify key biomarkers. These computational methods are improving the accuracy of identifying virus-host and bacteria-bacteria interactions, facilitating the development of diagnostic tools and therapeutic strategies. The resulting insights are crucial for advancing our understanding of infectious diseases and microbial ecology.