`sdrf-pipelines` is the official SDRF file validator and converts SDRF to pipeline configuration files
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Updated
May 16, 2025 - Python
`sdrf-pipelines` is the official SDRF file validator and converts SDRF to pipeline configuration files
autoprot provides standardised, fast, and reliable proteomics data analysis while ensuring a high customisability needed to tailor the analysis pipeline to specific experimental strategies.
Protein Cleaver is a versatile tool for protein analysis and digestion.
📊 User-friendly mass spectrometry and chromatography data analysis app for non-specialists with UI, graphing, quantification, MS/MS and data export capabilities
HIquant: An algorithm for quantifying homologous proteins and proteoforms from bottom-up mass-spec data
Map residue numbers from experimental protein structures to primary protein sequences and calculate the relative solvent accessibility of each residue
GRaph-based Analysis of Subcellular/Spatial Proteomics
Generate annotated Peptide Spectrum Matches (PSMs) from proteomic database search result
a molecular solutions toolbox for molecular biologists.
Mass spectrometry-based chemoproteomics pipeline for analyzing electrophile selectivity and identifying chemoproteomics detected amino acids (CpDAAs)
Tools for preprocessing and normalizing results of MaxQuant experiments and their respective controls from a run by normalizing data from the output peptides.txt file.
Extract the identified peptides and proteins from spectral library search of DIA proteomic data in Skyline
Code used for processing proteomics data associated with the publication by Yan et al., submitted to Nature Communications in 2024
GUI based on the alpaca proteomics pipeline for Absolute Protein Quantification data analysis
In Silico Trypsin/Lys-C Clevage Site Prediction
A simple GUI version of PyOpenMSs Mass Decomposition (https://pyopenms.readthedocs.io/en/latest/user_guide/mass_decomposition.html)
Python-powered app, created for Bradford Data Analysis, brought to you by Pandas and Matplotlib - all seamlessly delivered through Streamlit 💫
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