A tool for semi-automatic cell type classification

Contrastive pre-training for technology-agnostic single-cell representations beyond reconstruction

https://www.sc-best-practices.org

Lab Materials for MIT 6.S191: Introduction to Deep Learning

[ICCV 2025] Official PyTorch Code for "ModalTune: Fine-Tuning Slide-Level Foundation Models with Multi-Modal Information for Multi-task Learning in Digital Pathology"

Cell2Sentence: Teaching Large Language Models the Language of Biology

[ICCV 2025] COIN: Confidence Score-Guided Distillation for Annotation-Free Cell Segmentation

Codebase for "A Foundation Model for Cell Segmentation"

CellViT: Vision Transformers for Precise Cell Segmentation and Classification

Spatial gene expression at single-cell resolution from histology using deep learning with GHIST

📖 A curated list of resources dedicated to Natural Language Processing (NLP)

BiomedParse: A Foundation Model for Joint Segmentation, Detection, and Recognition of Biomedical Objects Across Nine Modalities

ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy

21 Lessons, Get Started Building with Generative AI

Unix, R and python tools for genomics and data science

The code repository of the paper: Competition and Attraction Improve Model Fusion

Foundation Model for Multiplex Spatial Proteomic Images

Challenge for multimodal data (transcriptomic, radiology, clinical)

Khoa hoc cua thay loi va Advanced VNPathoinformatics

PEKA：Teaching pathology foundation models to accurately predict gene expression with parameter efficient knowledge transfer

Solid Tumor Associative Modeling in Pathology

The Official Repository of VisionFM

An open source implementation of CLIP.

List of pathology feature extractors and foundation models