All Competitors
Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1–8 of 8 filtered models
mir-SFM
—2—Foundation model that predicts microRNA-mRNA target specificity from sequence, using a dual-encoder trained with a symmetric contrastive objective.
RNA25Opennessdrug-SFM
—1—Specificity foundation model predicting small-molecule drug-target binding from sequence, scored as cross-modal retrieval without docking or assays.
Small molecule16OpennessmhcSFM
—2—Peptide-MHC binding specificity model that frames presentation as cross-modal retrieval, aligning peptide and MHC encoders by contrastive learning.
Protein23Opennesstf-SFM
—2—Transcription factor-DNA binding specificity prediction from sequence, with a physics-derived dual-encoder trained by symmetric contrastive learning.
DNA & Gene18OpennesscrisprSFM
—2—CRISPR off-target prediction model that scores gRNA-DNA specificity from sequence, framing guide-target recognition as cross-modal retrieval.
DNA & Gene19Opennessenzyme-SFM
—2—Enzyme-substrate specificity model that scores catalytic pairs from sequence with a physics-derived dual-encoder and a contrastive objective.
Protein23OpennessCALM-1.0
—3—Contrastive antibody language model predicting antibody-antigen binding specificity from sequence with a dual-encoder, cross-attentive architecture.
Protein10Openness- National University of Singapore +1 otherMarch 8, 2025cardiologyclinical_reasoningdiagnosis_grounding+7
Multimodal LLM unifying 12-lead ECG time series, ECG images, and text for grounded, clinician-aligned electrocardiogram interpretation.
BiosignalsLanguage model79Openness