---
title: "Provenance-backed foundation model enrichment batch 2."
task: ""
lineage_type: import
upstream_source: https://github.com/inoue0426/awesome-computational-biology/blob/7a064bf0/data/enrichment.foundation-models-v2.yml
upstream_sha: 7a064bf0
imported_at: 2026-08-08
prompt_class: catalogue
upstream_changes: accepted
author: upstream
validated: false
---

# Provenance-backed foundation model enrichment batch 2.
resources:
  nicheformer:
    entities: [cell, gene, tissue]
    methods: [self-supervised-learning, transformer]
    modalities: [single-cell-rna-seq, spatial-transcriptomics, transcriptomics]
    tasks: [foundation-model-pretraining, representation-learning]
    year: 2024
    github: https://github.com/theislab/nicheformer
    paper: https://doi.org/10.1101/2024.04.15.589472
    last_checked: 2026-08-08
    metadata_sources:
      - https://github.com/theislab/nicheformer
      - https://doi.org/10.1101/2024.04.15.589472

  genept:
    entities: [cell, gene]
    methods: [language-model]
    modalities: [single-cell-rna-seq, transcriptomics]
    tasks: [batch-correction, classification, representation-learning]
    year: 2023
    github: https://github.com/yiqunchen/GenePT
    paper: https://www.biorxiv.org/content/10.1101/2023.10.16.562533v2
    last_checked: 2026-08-08
    metadata_sources:
      - https://github.com/yiqunchen/GenePT
      - https://www.biorxiv.org/content/10.1101/2023.10.16.562533v2

  scgpt_spatial:
    entities: [cell, gene, tissue]
    methods: [generative-model, self-supervised-learning, transformer]
    modalities: [multi-omics, single-cell-rna-seq, spatial-transcriptomics]
    tasks: [foundation-model-pretraining, imputation, representation-learning]
    year: 2025
    github: https://github.com/bowang-lab/scGPT-spatial
    paper: https://www.biorxiv.org/content/10.1101/2025.02.05.636714v1
    last_checked: 2026-08-08
    metadata_sources:
      - https://github.com/bowang-lab/scGPT-spatial
      - https://www.biorxiv.org/content/10.1101/2025.02.05.636714v1

  scprint:
    entities: [cell, gene]
    methods: [self-supervised-learning, transformer]
    modalities: [single-cell-rna-seq, transcriptomics]
    tasks:
      - batch-correction
      - cell-type-annotation
      - foundation-model-pretraining
      - gene-regulatory-network-inference
      - imputation
      - representation-learning
    year: 2025
    github: https://github.com/cantinilab/scPRINT
    documentation: https://www.jkobject.com/scPRINT/
    paper: https://www.nature.com/articles/s41467-025-58699-1
    last_checked: 2026-08-08
    metadata_sources:
      - https://github.com/cantinilab/scPRINT
      - https://www.nature.com/articles/s41467-025-58699-1