| Abstract |
Recombinant antibodies are indispensable biological materials in disease diagnosis, medical applications, and basic research. As to infectious diseases, antibodies can be used in therapy to control infections and applied to diagnostic tools for efficient disease diagnosis. However, traditional approaches for antibody preparation and selection are time-consuming and labor-intensive. Moreover, the screening for target antibodies from thousands of candidates is rather random and the binding affinity and specificity of antibody are often difficult to evaluate and optimize in time. Taking advantage of the advanced development of artificial intelligence, machine learning models will be introduced herein to facilitate the production and selection of the recombinant antibodies with optimized affinity. Subsequently, the recombinant antibodies will be chemically modified for further applications such as microfluidic chips and rapid tests. |
