PredSL combines several methods in order to predict a protein's localization to the chloroplast and the thylakoids, the mitochondrion and the secretory pathway.
As input PredSL requires the protein's sequence in fasta format.
The algorithm cosists of 10 steps:

Initially the 100 N-terminal residues of the sequence are coded (see supplementary material-neural network training) and fed to a first layer of 2 neural networks which determine whether a residue belongs or not to a chloroplast transit peptide (cTP) or a mitochondrial transit peptide (mTP). From this step we get 100 scores (one per residue) from each network.

We have set a cutoff where the residues do not belong to a transit peptide any longer, and thus we calculate two approximate cleavage sites from the 100 scores we calculated in step 1.(One from each network)

We take a window of 40 positions around the approximate cleavage site we estimated in step 2, and we use a set of neural networks to predict the cleavage site. Therefore we have one prediction of the cleavage site of the hypothetical cTP and one for the mTP.

We calculate the average of the scores of the hypothetical peptides predicted from each network, and this results to two scores.

We feed the 100 scores from step 1 to two neural networks (one for the cTP and one for the mTP), and we get two more scores. These scores represent the probability that the sequence has an mTP or a cTP.

We use PrediSi to calculate one more score for each sequence. This score represents the probability of a sequence belonging to a secreted protein.

We use a program that uses Markov chains to discriminate between two categories to get 6 more scores for the plant proteins and 3 more for the nonplant. (See supplementary material-Markov chains)

We use HMMER to get two additional scores for each protein. One that shows the existence or not of a cTP and one that shows the existence or not of an mTP.

We feed all the scores we gathered (13 for the plant and 7 for the non-plant proteins) to a neural network that does the final prediction.

Finally, if a sequence is predicted to belong to a chloroplast protein, we use HMMER to determine the existence of a lumenal-transit peptide (lTP)

STEP 10:
If the user requires it, PredSL provides the possibility to make a graph for each case. The graphs for the chloroplast and mitochondrial sequences are created using the scores from Step 1 and taking a window around the predicted cleavage site from Step 3. For the secreted proteins, the graphs are created usind the hydrophobicity index (Kytte-Doolittle, 1982) for a window around the predicted cleavage site from PrediSi.