{"id":24557963,"url":"https://github.com/singjc/redeem","last_synced_at":"2026-02-22T08:17:23.253Z","repository":{"id":265198455,"uuid":"870263744","full_name":"singjc/redeem","owner":"singjc","description":"Repository for Deep Learning Models for Mass Spectrometry written in Rust","archived":false,"fork":false,"pushed_at":"2025-06-06T16:42:29.000Z","size":584,"stargazers_count":13,"open_issues_count":0,"forks_count":1,"subscribers_count":5,"default_branch":"master","last_synced_at":"2025-06-06T17:35:31.973Z","etag":null,"topics":["deep-learning","mass-spectrometry","rust","semi-supervised-learning"],"latest_commit_sha":null,"homepage":"","language":"Rust","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/singjc.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2024-10-09T18:13:53.000Z","updated_at":"2025-06-06T16:42:31.000Z","dependencies_parsed_at":"2025-02-08T06:23:22.907Z","dependency_job_id":"ad698b94-f0b4-440e-afe1-b31fd0443d9e","html_url":"https://github.com/singjc/redeem","commit_stats":null,"previous_names":["singjc/redeem"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/singjc/redeem","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/singjc%2Fredeem","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/singjc%2Fredeem/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/singjc%2Fredeem/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/singjc%2Fredeem/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/singjc","download_url":"https://codeload.github.com/singjc/redeem/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/singjc%2Fredeem/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279019073,"owners_count":26086516,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-14T02:00:06.444Z","response_time":60,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deep-learning","mass-spectrometry","rust","semi-supervised-learning"],"created_at":"2025-01-23T05:31:28.673Z","updated_at":"2025-10-14T11:35:15.400Z","avatar_url":"https://github.com/singjc.png","language":"Rust","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n  \u003cpicture\u003e\n    \u003csource media=\"(prefers-color-scheme: dark)\" srcset=\"https://github.com/singjc/redeem/raw/master/img/redeem_logo.png\" alt=\"ReDeem_Logo\" width=\"500\"\u003e\n    \u003csource media=\"(prefers-color-scheme: light)\" srcset=\"https://github.com/singjc/redeem/raw/master/img/redeem_logo.png\" alt=\"ReDeem_Logo\" width=\"500\"\u003e\n    \u003cimg alt=\"ReDeem Logo\" comment=\"Placeholder to transition between light color mode and dark color mode - this image is not directly used.\" src=\"https://github.com/singjc/redeem/raw/master/img/redeem_logo.png\"\u003e\n  \u003c/picture\u003e\n\u003c/p\u003e\n\n---\n\n# ReDeeM: Repository for Deep Learning Models for Mass Spectrometry\n\nReDeeM is a Rust crate designed for implementing deep learning models specifically tailored for mass spectrometry data. The primary goal of this project is to facilitate the prediction of peptide properties and to develop classifier scoring models (TDA). \n\n### Usage\n\nThe ReDeeM crates are designed to be used as a library in other projects, i.e. in Sage. To use the ReDeeM crates, add the following to your `Cargo.toml` file:\n\n```toml\n[dependencies]\nredeem-properties = { git = \"https://github.com/singjc/redeem.git\", branch = \"master\" }\nredeem-classifiers = { git = \"https://github.com/singjc/redeem.git\", branch = \"master\" }\n```\n\n**Note**: The ReDeeM crates are still under development and are not yet available on crates.io.\n\n### Current Crates\n\nThe ReDeeM project consists of two primary crates:\n\n1. **redeem-properties**: \n   - This crate focuses on deep learning models for peptide property prediction. It implements models for predicting retention time (RT), ion mobility (IM), and MS2 fragment intensities using the Candle library.\n   - The models can be trained, fine-tuned on new data and can be saved in the safetensor format for later use.\n   \n   - Current Models\n  \n    Model | Name | Architecture | Implemented\n    --- | --- | --- | ---\n    AlphaPept RT Model | `rt_cnn_lstm` | CNN-LSTM | :heavy_check_mark:\n    AlphaPept MS2 Model | `ms2_bert` | Bert | :heavy_check_mark:\n    AlphaPept CCS Model | `ccs_cnn_lstm` | CNN-LSTM | :heavy_check_mark:\n    RT Model | `rt_tf_lstm` | CNN-Transformer | :heavy_check_mark:\n    CCS Model | `ccs_tf_lstm` | CNN-Transformer | :heavy_check_mark:\n\n2. **redeem-classifiers**:\n   - This crate is aimed at developing semi-supervised scoring classifier models. The goal is to create models for separating target peptides from decoys.\n  \n   - Current Models\n  \n    Model | Name | Architecture | Implemented\n    --- | --- | --- | ---\n    XGBoost Classifier | `redeem_classifiers::XGBoostClassifier` | XGBoost | :heavy_check_mark:\n    GBDT Classifier | `redeem_classifiers::GBDTClassifier` | GBDT | :heavy_check_mark:\n    SVM Classifier | `redeem_classifiers::SVMClassifier` | SVM | :heavy_check_mark:\n\n\u003e [!NOTE]\n\u003e To use the XGBoost classifier, or the SVM classifier, you need to compile with the `--features xgboost` or `--features linfa` flag respectively.\n\n\u003e [!IMPORTANT]\n\u003e The XGBoost crate is a wrapper around the original XGBoost library, which requires clang/c++ to be installed on the system. On Ubuntu, you can do the following:\n    \n    ```bash\n    sudo apt update\n    sudo apt install build-essential\n    sudo apt install clang\n    sudo apt install libstdc++-12-dev\n    ```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsingjc%2Fredeem","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsingjc%2Fredeem","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsingjc%2Fredeem/lists"}