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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 2329–2335 of 2335 models
Chromatin feature prediction from 2 kb of DNA, scoring 2,002 transcription factor, DNase and histone profiles to rank noncoding variant effects.
Nucleus instance segmentation for fluorescence microscopy and H&E histology, predicting a star-convex polygon per pixel to separate crowded nuclei.
Dilated convolutional network that predicts cell-type-specific epigenetic and transcriptional profiles from DNA sequence across mammalian genomes.
Visible neural network simulating eukaryotic cell growth by embedding the Gene Ontology into its architecture for interpretable phenotype prediction.
Attention-based model predicting gene expression from histone modification signals across 56 cell types, with interpretable attention scores.
Convolutional neural network that predicts DNA accessibility from sequence across 164 DNase-seq cell types, enabling variant effect prediction.
Noncoding variant effect prediction from DNA sequence, scoring how an allele shifts 919 chromatin features across ENCODE and Roadmap cell types.