Deepaprot: deep learning based abiotic stress protein sequence classification and identification tool in cereals

HIGHLIGHTS

  • who: Bulbul Ahmed et al. from the Agriculture and Forestry University, Tulane University, United States have published the research work: DeepAProt: Deep learning based abiotic stress protein sequence classification and identification tool in cereals, in the Journal: (JOURNAL)
  • what: During the model compilation, an Adam optimizer and mean square error loss function were used with 500 epochs. The authors proposed a novel activation function name SIELU which was used to build the DL model along with other hyperparameters.
  • how: For the binary classification of four different abiotic datasets the authors used a precision . . .

     

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