CPred: A deep learning framework for predicting the charge state distribution in modified and unmodified peptides in ESI
Project description
CPred: Charge State Prediction for Modified and Unmodified Peptides in Electrospray Ionization
Introduction
CPred is a neural network capable of predicting the charge state distribution for modified and unmodified peptides in electrospray ionisation. By summarising the modifications as measures of mass and atomic compositions, the model is capable of generalising unseen modifications during training.
The model is available as a Python package, installable through Pypi and conda. This also makes it possible to use from the command-line-interface.
How to use
Python package
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