Fig. 5
From: Modeling aspects of the language of life through transfer-learning protein sequences
Prediction tasks’ architectures. On the left the architecture of the model used for the per-residue level predictions (secondary structure and disorder) is sketched, on the right that used for per-protein level predictions (localization and membrane/not membrane). The ‘X’, on the left, indicates that different input features corresponded to a difference in the number of input channels, e.g. 1024 for SeqVec or 50 for profile-based input. The letter ‘W’ refers to the window size of the corresponding convolutional layer (W = 7 implies a convolution of size 7 × 1)