Quantitative mass spectrometry workflow. Currently supports proteomics experiments with complex experimental designs for DDA-LFQ, DDA-Isobaric and DIA-LFQ quantification.
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Updated
Jun 6, 2026 - Nextflow
Quantitative mass spectrometry workflow. Currently supports proteomics experiments with complex experimental designs for DDA-LFQ, DDA-Isobaric and DIA-LFQ quantification.
Quantitative mass spectrometry workflow. Currently supports proteomics experiments with complex experimental designs for DDA-LFQ, DDA-Isobaric and DIA-LFQ quantification.
An open-source Python package for accurate and sensitive peptide and protein quantification.
A comprehensive R package for label-free proteomics data analysis and modeling
Reanalysis of Phaeodactylum tricornutum nitrogen-starvation proteome (PRIDE PXD033328, MaxQuant LFQ): cleaning + Perseus imputation, PCA/PLS-DA, differential proteins, on/off switch theme. Full R.
pipeline for TMT/LFQ proteomics: QC, volcano plots, and Reactome enrichment
Missing-value imputation benchmark for peptide-level LFQ proteomics. Evaluated on a spike-in dataset and via simulation.
🔍 Optimize multi-objective tasks with Tchebycheff scalarization for better alignment and efficient Pareto frontier exploration.
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