deepCE

Description

Co-fractionation mass spectrometry (CF-MS) has emerged as a powerful approach for cell-wide identification of protein complexes that performs nearly all biological processes and cellular activities. While computational tools based on traditional machine learning is widely applied to analyze protein complexes, it remains unclear if it is the most suitable choice for analyzing CF/MS dataset. Here, we introduce deepCE, a R/Bioconductor package that employs deep learning approaches for automated scoring of co-fractionation mass spectrometry (CF-MS) and sophisticated clustering procedure for network inference of underlying complexes.

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• Matineh Rahmatbakhsh author trl maintainer
• Mohan Babu led
• Alla Gagarinova led