mims-harvard/CASCADE-Alzheimer
https://huggingface.co/mims-harvard/CASCADE-AlzheimerCASCADE: context-aware single-cell modelling links cellular programmes to patient-level disease phenotypes
Sourced from
- HuggingFace — mims-harvard/CASCADE-Alzheimer
Related resources
jlu-wsj/scRep
by jlu-wsjscRep is a PyTorch model for extracting cell embeddings from single-cell RNA-seq AnnData (.h5ad) inputs. This repository is a standalone Hugging Face release bundle: it includes checkpoint weights, the exact paired gene vocabulary, the inference implementation, and runnable examples.
theislab/Nicheformer
by theislabNicheformer is a transformer-based model designed for understanding and predicting cellular niches and their interactions. The model uses masked language modeling to learn representations of cellular contexts and their relationships.
tahoebio/Tahoe-x1
by tahoebioTahoe-x1 is a family of perturbation-trained single-cell foundation models with up to 3 billion parameters, developed by Tahoe Therapeutics. Pretrained on 266 million single-cell transcriptomic profiles including the Tahoe-100M perturbation compendium, Tahoe-x1 achieves state-of-the-art performance…
zhangtaolab/plant-dnabert-6mer
by zhangtaolabThe plant DNA large language models (LLMs) contain a series of foundation models based on different model architectures, which are pre-trained on various plant reference genomes. All the models have a comparable model size between 90 MB and 150 MB, BPE tokenizer is used for tokenization and 8000…
Sentinal4D/PhenoSeq
by Sentinal4DPhenoSeq is a Gaussian diffusion model that generates scGPT RNA-seq embeddings conditioned on ViT-L microscopy imaging features. Given fluorescence microscopy images of a cell or well, it predicts a 512-dimensional scGPT embedding representing the transcriptomic state of individual cells — enabling…
FremyCompany/BioLORD-2023-M
by FremyCompany# FremyCompany/BioLORD-2023-M This model was trained using BioLORD, a new pre-training strategy for producing meaningful representations for clinical sentences and biomedical concepts.