Vadim Demichev

quantmsdiann. quantms workflow for DIANN tool including DIA and DDA analysis

DE-LIMP. LIMPA DAVIS Proteomics Pipeline

slicepasef. Slice-PASEF method generator app written in R Shiny

quantms. Quantitative mass spectrometry workflow. Currently supports proteomics experiments with complex experimental designs for DDA-LFQ, DDA-Isobaric and DIA-LFQ quantification.

pepMAP. Python

Carafe. High quality in silico spectral library generation for data-independent acquisition proteomics

timsrust. Rust

Scalable-DIA-NN. Scalable workflow to run https://github.com/vdemichev/DiaNN on NCI Gadi HPC

oktoberfest. Rescoring and spectral library generation pipeline for proteomics.

AutoGPT. AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

RWKV-LM. RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.

rwkv.cpp. INT4/INT5/INT8 and FP16 inference on CPU for RWKV language model

llama.cpp. LLM inference in C/C++

PDD-shiny. Processing of DIA-NN Data

synthedia. Create synthetic DIA LC-MS/MS for proteomics experiments

advent-of-code-2022-with-chat-gpt. Solving Advent of Code 2022 with ChatGPT

stable-diffusion. A latent text-to-image diffusion model

sage. Proteomics search & quantification so fast that it feels like magic

DIAgui. An interactive shiny app for processing DIA-nn output (filtering, MaxLFQ, Top3, iBAQ, etc.)

Protein-Contaminant-Libraries-for-DDA-and-DIA-Proteomics. This project is created by the Hao Lab at the Department of Chemistry & Biochemistry, University of Maryland, College Park, MD. This project aims to provide contaminant protein FASTA and spectral libraries that can be universally applied to DDA and DIA proteomics and freely accessible for the proteomics community.

casanovo. De Novo Mass Spectrometry Peptide Sequencing with a Transformer Model

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

msdap. MS-DAP: downstream analysis pipeline for quantitative proteomics

esquisse. RStudio add-in to make plots interactively with ggplot2

DiaNN. DIA-NN - a universal automated software suite for DIA proteomics data analysis.

MiniDNN. A header-only C++ library for deep neural networks

pDeep3. MS/MS prediction for peptides

proteomics-sample-metadata. SDRF: The Proteomics sample metadata: Standard for experimental design annotation in proteomics datasets

torchnca. A PyTorch implementation of Neighbourhood Components Analysis.

pyphe. Python toolbox for phenotype analysis of arrayed microbial colonies

DeepDIA. Using deep learning to generate in silico spectral libraries for data-independent acquisition analysis.

FragPipe. A cross-platform proteomics data analysis suite

auto-py-to-exe. Converts .py to .exe using a simple graphical interface

Proteomics_linear_modeling. Short workshop to demonstrate some uses of linear modeling in proteomics

prosit. Prosit offers high quality MS2 predicted spectra for any organism and protease as well as iRT prediction. When using Prosit is helpful for your research, please cite "Gessulat, Schmidt et al. 2019" DOI 10.1038/s41592-019-0426-7