All Competitors
Every biological foundation model, evaluated and ranked by the bio.rodeo team
Applications
Architectures
Learning Paradigms
Biological Subjects
Showing 1–7 of 7 filtered models
AlphaGenome
Google DeepMind
Google DeepMind model that predicts thousands of functional genomic tracks at single base-pair resolution from megabase-scale DNA sequences.
Borzoi
Calico Life Sciences
Deep learning model predicting cell-type-specific RNA-seq coverage at 32 bp resolution from 524 kb of DNA sequence, jointly modeling transcription, splicing, and polyadenylation.
GeneCompass
Chinese Academy of Sciences
Knowledge-informed cross-species foundation model pre-trained on 101M human and mouse single-cell transcriptomes to decipher universal gene regulatory mechanisms.
gLM
Harvard University / MIT
Genomic language model trained on metagenomic scaffolds that learns protein co-regulation and function by modeling gene context and operon structure.
EpiGePT
Tsinghua University
Transformer model predicting context-specific epigenomic signals across cell types using DNA sequence and transcription factor activity profiles.
Species-Aware DNA Language Model
Technical University of Munich
Masked DNA language model trained on 800+ species spanning 500M years of evolution, using explicit species conditioning to capture conserved regulatory elements.
Enformer
Google DeepMind
Transformer model that predicts gene expression and regulatory activity from 200kb DNA sequences, capturing enhancer-promoter interactions up to 100kb away.