All Competitors

Every biological foundation model, evaluated and ranked by the bio.rodeo team

Showing 1–12 of 12 filtered models

  • MethylSeqNet

    ———
    University of California, Berkeley +1 otherJune 7, 2026chromatin_accessibility_predictiondna_methylationepigenetics+6

    Gene regulation model that conditions a pretrained DNA sequence embedding on CpG methylation to capture cell-type and allele-specific regulation.

    DNA & Gene
    18Openness

  • MethylProphet

    —2—
    Columbia UniversityFebruary 17, 2026dna_methylationepigenomicsfoundation_model+4

    Transformer that infers whole-genome DNA methylation from gene expression, generalizing zero-shot to unmeasured CpG sites and unseen samples.

    DNA & Gene
    10Openness

  • ISTS

    ———
    New York UniversityDecember 2, 2025autoencoderbertcancer_classification+9

    Pan-cancer multi-omic foundation model encoding CpG-island DNA methylation and RNA-seq for zero-shot cancer classification and mutation prediction.

    Single-cellDNA & Gene
    20Openness

  • Melody

    ———
    Shandong University +2 othersNovember 23, 2025cnndna_methylationepigenomics+5

    Deep learning framework that predicts DNA methylation from genomic sequence across 39 human tissues, with an scRNA-seq variant for unseen cell types.

    DNA & Gene
    8Openness

  • MOJO

    40—45
    InstaDeepJune 25, 2025bertdna_methylationfoundation_model+7

    Bimodal masked language model that jointly encodes bulk RNA-seq expression and DNA methylation into patient-level embeddings for cancer genomics.

    RNADNA & Gene
    29Openness

  • scDNAm-GPT

    202—
    Guangzhou Medical University +1 otherFebruary 23, 2025cell_type_annotationcross_attentiondna_methylation+5

    Single-cell DNA methylation foundation model capturing genome-wide CpG dependencies in whole-genome bisulfite sequencing across tissues and species.

    Single-cellDNA & Gene
    78Openness

  • MuLan-Methyl

    7105
    University of TübingenJuly 25, 2023dna_methylationepigenomic_predictionepigenomics+5

    Multi-language transformer framework using five pre-trained language models to predict DNA methylation (6mA, 4mC, 5hmC) across species.

    DNA & Gene
    89Openness

  • mEthAE

    34—
    Wageningen University & ResearchJuly 18, 2023autoencoderdna_methylationepigenomic_prediction+3

    Chromosome-wise explainable autoencoder that compresses DNA methylation array data up to 400-fold while keeping CpG groupings interpretable.

    DNA & Gene
    47Openness

  • iDNA-ABF

    15141—
    Shandong UniversityOctober 17, 2022dna_methylationepigenomic_predictionepigenomics+4

    DNA language model for interpretable prediction of 4mC, 5hmC, and 6mA methylation sites across species, using multi-scale k-mer BERT encoders.

    DNA & Gene
    53Openness

  • INTERACT

    1125—
    Lieber Institute for Brain DevelopmentAugust 16, 2022deep_learningdna_methylationepigenomic_prediction+4

    Deep learning model predicting DNA methylation regulatory variants at CpG sites in the human brain, fine-mapping psychiatric disorder risk loci.

    DNA & Gene
    9Openness

  • BERT6mA

    516—
    Kyushu Institute of TechnologyMarch 10, 2022dna_methylationepigenomic_predictionepigenomics+4

    BERT-based predictor of DNA N6-methyladenine (6mA) modification sites, using word2vec encoding and cross-species transfer learning.

    DNA & Gene
    45Openness

  • CpG Transformer

    3921—
    Ghent UniversityJanuary 12, 2022dna_methylationdna_methylation_imputationepigenomic_prediction+4

    Transformer that imputes missing CpG methylation states from sparse single-cell bisulfite sequencing, modeling genomic and cell-level structure.

    DNA & Gene
    79Openness