DeepSig Signal Peptide Prediction
Predict signal peptides and cleavage sites in protein sequences.
Overview
DeepSig predicts N-terminal signal peptides, distinguishes transmembrane and other proteins, and estimates signal peptide cleavage sites using organism-specific neural-network and cleavage ensembles.
Run DeepSig Signal Peptide Prediction on Neurosnap
The DeepSig Signal Peptide Prediction online webserver allows anybody with a Neurosnap account to run and access DeepSig Signal Peptide Prediction, no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong Terms of Use and Privacy Policy.
Features
- Choose models for eukaryotes, Gram-positive bacteria, or Gram-negative bacteria.
- Classify proteins as signal peptide, transmembrane, or other.
- Locate predicted signal peptide cleavage sites and inspect ensemble residue votes.
- Download prediction CSVs and FASTA sequences for predicted mature proteins.
Statistics
Neurosnap periodically calculates runtime statistics based on job execution data. These estimates provide a general guideline for how long your job may take, but actual runtimes can vary significantly depending on factors like input size or settings used.
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API Request
Access DeepSig Signal Peptide Prediction using the Neurosnap API by sending a request using any programming language with HTTP support. To safely generate an API key, visit the API tab of your overview page.
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Citations
Please cite the original work when using DeepSig Signal Peptide Prediction in publications or research outputs.
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Savojardo C, Martelli PL, Fariselli P, Casadio R. DeepSig: deep learning improves signal peptide detection in proteins. Bioinformatics 34(10), 1690–1696 (2018). https://doi.org/10.1093/bioinformatics/btx818. |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |