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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 1–7 of 7 filtered models
RNA foundation model pretrained on 223 eCLIP experiments to predict base-resolution RBP binding, with frozen embeddings that transfer downstream.
RNA-binding protein predictor trained on eCLIP data that scores binding intensity along transcripts and recovers motifs via integrated gradients.
RNA language model that reads full-length transcripts up to 10,000 nucleotides, pairing bidirectional state space layers with multi-head attention.
RNA-binding protein binding profiles predicted base by base across 800 bp windows, with an m6A signal channel that exposes methylation-RBP crosstalk.
RNA foundation models that learn their own character-level tokenization instead of fixed nucleotide or k-mer vocabularies. Sizes run 8M to 650M.
RNA-binding protein affinity prediction at single-base resolution from sequence alone. One model spans 155 RBP targets across three cell lines.
Predicts CLIP-seq crosslink counts along an RNA sequence base by base, separating protein-specific signal from experimental background.