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USPNet Signal Peptide Prediction

Predict six signal-peptide classes and candidate cleavage sites with USPNet using uploaded multiple-sequence alignments.

Overview

Predict six signal-peptide classes and candidate cleavage sites with USPNet using uploaded multiple-sequence alignments.

Run USPNet Signal Peptide Prediction on Neurosnap

The USPNet Signal Peptide Prediction online webserver allows anybody with a Neurosnap account to run and access USPNet 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.

USPNet Signal Peptide Prediction service preview

Features

  • Classify proteins as no signal peptide, Sec/SPase I, Sec/SPase II, Tat/SPase I, Tat/SPase II, or Sec/SPase IV.
  • Use a model with known organism information or an organism-agnostic checkpoint.
  • Inspect N-terminal residue labels and candidate cleavage positions.
  • Download CSV results and predicted mature protein sequences.

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 USPNet 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 USPNet Signal Peptide Prediction in publications or research outputs.

Shen J, Yu Q, Chen S, Tan Q, Li J, Li Y. Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model. Nature Computational Science 4, 29–42 (2024).

Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/

Set up your run

Configure USPNet Signal Peptide Prediction

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Inputs & configuration

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