A list of tools on proteomics using deep learning

Template for nbdev projects

An open-source Python package for the visual annotation of proteomics data with sequence specific knowledge.

GLEAMS is a Learned Embedding for Annotating Mass Spectra.

Large-scale tandem mass spectrum clustering using fast nearest neighbor searching.

Spectral library searching using approximate nearest neighbor techniques.

Jigsaw-like AggMap: A Robust and Explainable Multi-Channel Omics Deep Learning Tool

Kaggle Python docker image

DeepLC: Retention time prediction for peptides carrying any modification.

A python library for multi omics included bulk, single cell and spatial RNA-seq analysis.

Evolutionary Scale Modeling (esm): Pretrained language models for proteins

Self-supervised learning of molecular representations from millions of tandem mass spectra using DreaMS (Nat Biotechnology)

Proteomics Mass Spectrometry Datasets for Machine Learning

Rescoring and spectral library generation pipeline for proteomics.

Democratizing ML in proteomics

Open source code for AlphaFold 2.

Tensors and Dynamic neural networks in Python with strong GPU acceleration