Figure 1.
Input features and architecture of DPAM-AI. (A) AlphaFold model of Q5ZSU4 colored in rainbow (top), distance matrix to represent inter-residue distances in the 3D space (left), and PAE matrix to represent the estimated errors in the predicted distances between residues. (B) A 2D matrix to represent evidence derived from similar ECOD domains to the query protein found by Hhsuite sequence comparisons. (C) A 2D matrix to represent the evidence derived from similar ECOD domains to the query protein found by Dali 3D structure comparisons. (D) Histograms showing the distribution of domain numbers per protein in the training and testing datasets. (E) The DPAM-AI architecture.

Input features and architecture of DPAM-AI. (A) AlphaFold model of Q5ZSU4 colored in rainbow (top), distance matrix to represent inter-residue distances in the 3D space (left), and PAE matrix to represent the estimated errors in the predicted distances between residues. (B) A 2D matrix to represent evidence derived from similar ECOD domains to the query protein found by Hhsuite sequence comparisons. (C) A 2D matrix to represent the evidence derived from similar ECOD domains to the query protein found by Dali 3D structure comparisons. (D) Histograms showing the distribution of domain numbers per protein in the training and testing datasets. (E) The DPAM-AI architecture.

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