All Competitors
Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1–13 of 13 filtered models
Lingshu-Cell
—3—Virtual cell model using masked discrete diffusion over the whole transcriptome to simulate scRNA-seq perturbation responses across tissues.
Single-cell21OpennessSCALE
———Virtual cell foundation model predicting single-cell responses to genetic, chemical, and cytokine perturbations with conditional flow matching.
Single-cell19OpennessAetherCell
202—Generative virtual-cell model predicting whole-transcriptome responses to unseen compounds and genetic perturbations, from cell lines to organoids.
Single-cellSmall molecule29OpennessMAP
———Shanghai Jiao Tong UniversityFebruary 25, 2026contrastive_learningdrug_response_predictiongraph_neural_network+6Knowledge-graph-grounded model that predicts single-cell transcriptomic responses to small molecules, with zero-shot prediction for unprofiled drugs.
Single-cellSmall molecule12OpennessSTACK
14211—Single-cell foundation model using tabular attention over context cells to predict responses to arbitrary perturbations without fine-tuning.
Single-cell33OpennessCellHermes
30276Single-cell foundation model adapting LLaMA-3.1-8B with LoRA, recasting transcriptomes and protein interaction networks as natural-language Q&A pairs.
Single-cellRNA55OpennessCellTok
———Multimodal LLM that tokenizes single cells into discrete VQ-VAE codebook tokens, letting one model reason jointly over transcriptomes and text.
Single-cellLanguage model20OpennessShusi
11—Single-cell foundation model inferring context-specific protein-protein interactions from cancer transcriptomes via a variational graph autoencoder.
Single-cellProtein20OpennessSCimilarity
258125—Single-cell foundation model trained by metric learning to embed scRNA-seq profiles for cell type annotation and similarity search in cell atlases.
Single-cell78OpennessGEARS
386376—Perturbation prediction model that forecasts transcriptional responses to multi-gene CRISPR perturbations from scRNA-seq and a gene-gene graph.
Single-cell68OpennessscTranslator
978—Generative transformer that translates single-cell transcriptomes into proteomes, inferring missing protein abundance from RNA expression alone.
Single-cell33OpennesstGPT
1762159Tianjin Medical University Cancer Institute and HospitalApril 20, 2023cell_type_annotationfoundation_modellanguage_model+4Single-cell foundation model pre-trained on 22 million transcriptomes, using rank-based gene encoding for clustering and trajectory inference.
Single-cell50Openness