Vaxi-DL is a web-based deep learning (DL) tool designed for rapid and accurate prediction of vaccine candidates. It assesses individual protein sequences for bacterial, protozoan, fungal, and viral models associated with human infectious diseases. Utilizing 18 biological and 9154 physicochemical properties, Vaxi-DL combines deep learning and immunoinformatics, demonstrating high speed, sensitivity, and accuracy. It addresses the complex and time-consuming process of vaccine development by expediting the identification of potential antigens.
TRY OUR TOOLVax-Elan innovative data-driven methods, including reverse vaccinology and machine learning, for vaccine design. The authors introduce an integrated framework for identifying vaccine candidates, emphasizing neglected tropical diseases like Chagas. They employ computational techniques to target Trypanosoma cruzi, proposing a multi-epitope vaccine.
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