Fig. 5

DMPfold predictions are robust to variations in MSA composition and sequence length. Evaluations are made on the Pfam validation set. a Correlation of TM-align score with alignment depth and effective sequence count N_eff, defined in the Methods section. The Pearson correlation coefficients are shown. DMPfold is able to generate accurate models for some Pfam families with fewer than 100 sequences in the sequence alignment. b There is little correlation of model accuracy with target sequence length. c In order to compare with ref. ¹⁹, we calculated the N_f with their criteria and plotted the mean model accuracy of models in bins of N_f values. N_f values were calculated as described in ref. ¹⁹, where an 80% identity threshold was used for clustering. Values were read off the graph in Fig. 2 of ref. ¹⁹ and added here. It is important to note that the proteins used to obtain our values were different to theirs. It can be seen that DMPfold is effective at lower effective sequence counts