DeepSig is a web-server for predicting signal peptides and their cleavage sites. DeepSig is based on deep learning methods, in particular Deep Convolutional Neural Networks (DCNNs), specifically designed to accurately identify signal peptide sequences located at the N-terminus of the query protein sequence. Furthermore, DeepSig is optimized to discriminate between true signal peptides and similar N-terminal transmembrane segments. When a signal sequence is detected, the query sequence is analyzed by a probabilisic sequence labelling method (based on Conditional Random Fields) to identify the precise location of the cleavage site.

For details see: Savojardo C., Martelli P.L., Fariselli P., Casadio R. DeepSig: deep learning improves signal peptide detection in proteins, Bioinformatics (2018) 34(10): 1690-1696.

Submit your sequence(s)

Please, paste input FASTA sequences (max 500 sequences, max 400000 residues) in the area below:

Alternatively, select and upload a FASTA file:

Select the taxonomic origin of the input sequences: