Solstice-AI/C2S-Scale-Gemma-2-27B-Q8_0-GGUF

A foundation model over paired proteomic and transcriptomic expression. Attention between measured features yields a protein-protein association network without task-specific training.

PhenoSeq 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…

Nicheformer 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.

CASCADE: context-aware single-cell modelling links cellular programmes to patient-level disease phenotypes

Stack is a large-scale encoder-decoder foundation model for single-cell biology. It introduces a novel tabular attention architecture that enables both intra- and inter-cellular information flow, setting cell-by-gene matrix chunks as the basic input data unit.

Foundation models for genomics and transcriptomics pretrained on 3,000+ human genomes and 850+ diverse species, enabling chromatin accessibility prediction, splice site detection, and promoter classification across multiple model scales (InstaDeep, NVIDIA & TUM, Nature Methods 2023)