Figure 1From: A predicted physicochemically distinct sub-proteome associated with the intracellular organelle of the anammox bacterium Kuenenia stuttgartiensisPerformance comparison of the RF model trained on different types of input data. 500 RF models with randomly generated P1 and P2 sets, to correct for class A and P inbalance, were trained on each of the following 6 types of data: the full-length amino acid sequences, the signal peptides (SP) and the mature protein amino acid sequences, each analyzed with either the residue frequency of single amino acids or the frequency of 2 adjacent amino acids. When the 6 top-performing models of each input type are compared, the model trained with full-length protein sequences with the 2 adjacent amino acids combination shows the highest overall accuracy (89%) and A protein recall (90%).Back to article page