Here, we describe the use of TriNet to predict peptides with anticancer and antimicrobial properties by a tri-fusion neural network. We detail the use of TriNet for both the offline Python script version and the online service, thereby demonstrating its convenience for users. In addition, we provide a detailed explanation of the training process of TriNet to enhance the understanding of researchers seeking to leverage deep learning techniques for peptide classification. For complete details on the use and execution of this protocol, please refer to Zhou et al.1.
Keywords: Bioinformatics; Cancer; Computer Sciences; Microbiology; Sequence Analysis.
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