peptide-identification

modular & open DIA search

Protein Identification with Deep Learning

Collects software dedicated to predicting specific properties of peptides

Modular and user-friendly platform for AI-assisted rescoring of peptide identifications

MS²PIP: Fast and accurate peptide spectrum prediction for multiple fragmentation methods, instruments, and labeling techniques.

Ursgal - universal Python module combining common bottom-up proteomics tools for large-scale analysis

Pipeline for de novo peptide sequencing (Novor, DeepNovo, SMSNet, PointNovo, Casanovo) and assembly with ALPS.

Common utilities for parsing and handling peptide-spectrum matches and search engine results in Python

Parse ProForma 2.1 peptide sequences and calculate masses, fragments, and isotopic distributions in Python.

PepQuery: a targeted peptide search engine

Visualizing and Analyzing Mass Spectrometry Related Data in Proteomics

DelPi: Deep Learning-based Peptide Identification Search Engine

A tool for mass spectrometry data analysis.

DeepRescore: rescore PSMs leveraging deep learning-derived peptide features

PTM-Invariant Peptide Identification. An open search tool.

Predicts anticancer peptides using random forests trained on the n-gram encoded peptides. The implemented algorithm can be accessed from both the command line and shiny-based GUI.

A Multi-Representation Ensemble Learning Framework for Accurate Bitter Peptide Identification

MS Amanda is a scoring system to identify peptides out of tandem mass spectrometry data using a database of known proteins.

Protein Cleaver is a versatile tool for protein analysis and digestion.