PAMmla
Machine learning models to predict SpCas9 PAM preference from amino acid sequence.
Overview
PAMmla is a set of machine learning models to predict SpCas9 PAM preference from an amino acid sequence.
Run PAMmla on Neurosnap
The PAMmla online webserver allows anybody with a Neurosnap account to run and access PAMmla, 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
- Predicts SpCas9 PAM preference based on amino acid sequence.
- Utilizes three different pre-trained neural network models (trained on different data splits) to ensure robust predictions.
- Generates predictions for specific pCas9 amino acid variants.
- Accepts variants denoted as 6-character strings representing amino acids at positions 1135, 1136, 1218, 1219, 1335, 1337.
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 PAMmla 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 PAMmla in publications or research outputs.
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Silverstein, R.A., Kim, N., Kroell, AS. et al. Custom CRISPR–Cas9 PAM variants via scalable engineering and machine learning. Nature 643, 539–550 (2025). https://doi.org/10.1038/s41586-025-09021-y |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |