Biological models

107 model records in release 2026-09-30-e37e3ab1284d. Showing 73–96; page 4 of 5.

Evaluated configurations, methods and pipelines are listed separately. Names alone do not establish equivalent models or checkpoints.

• RhoMax

  Proteins and complexes

  Named prediction model family identified in the cited primary source. Exact fitted configurations and scores are separate records.

• RITA

  Proteins and complexes

  Named prediction model family identified in the cited primary source. Exact fitted configurations and scores are separate records.

• RNA-FM

  RNA and transcriptomes

  RNA-FM learns contextual representations of RNA nucleotides for downstream RNA analyses.

  Record: catalog-model-rna-fm

• RNA-FM

  RNA

  RNA-FM learns contextual representations of RNA nucleotides for downstream RNA analyses.

  Record: discovery-model-rna-fm

• S2F

  Proteins and complexes

  Named prediction model family identified in the cited primary source. Exact fitted configurations and scores are separate records.

• S2F-MSA

  Proteins and complexes

  Named prediction model family identified in the cited primary source. Exact fitted configurations and scores are separate records.

• S3F

  Proteins and complexes

  Named prediction model family identified in the cited primary source. Exact fitted configurations and scores are separate records.

• S3F-MSA

  Proteins and complexes

  Named prediction model family identified in the cited primary source. Exact fitted configurations and scores are separate records.

• SaProt

  Proteins and complexes

  Named prediction model family identified in the cited primary source. Exact fitted configurations and scores are separate records.

• scFoundation

  Cells and tissues

  scFoundation produces contextual cell and gene representations from gene-expression measurements.

• scGPT

  Cells and tissues

  scGPT learns representations of single-cell molecular measurements and supports task-specific adaptation.

  Record: catalog-model-scgpt

• scGPT

  Single cell

  scGPT learns representations of single-cell molecular measurements and supports task-specific adaptation.

  Record: discovery-model-scgpt

• scVI

  Cells and tissues

  scVI models single-cell RNA counts with a probabilistic latent-variable model that accounts for observed covariates.

  Record: catalog-model-scvi

• scVI

  Single cell

  scVI models single-cell RNA counts with a probabilistic latent-variable model that accounts for observed covariates.

  Record: discovery-model-scvi

• SegmentNT

  Genomics

  SegmentNT labels genomic elements at individual nucleotide positions using a pretrained DNA backbone.

• SiteRM

  Proteins and complexes

  Named prediction model family identified in the cited primary source. Exact fitted configurations and scores are separate records.

• SpliceAI

  DNA and genomes

  SpliceAI annotates sequence variants with predicted splice acceptor and donor changes.

  Record: catalog-model-spliceai

• SpliceAI

  Genomics

  SpliceAI annotates sequence variants with predicted splice acceptor and donor changes.

  Record: discovery-model-spliceai

• STATE

  Single cell

  State separates cellular representation learning from prediction of responses to perturbation.

• SweetNet

  Glycomics

  SweetNet predicts glycan properties and produces learned representations from glycan graphs.

• TAPE Bepler

  Protein function

  The TAPE Bepler comparison uses a protein representation that combines bidirectional language modelling with supervised structural pretraining.

• TAPE LSTM

  Protein function

  The TAPE LSTM baseline represents protein sequences using recurrent networks that read residues in both directions.

• TAPE ResNet

  Protein function

  The TAPE ResNet baseline represents protein sequences using residual convolutional blocks before a task-specific prediction head.

• TAPE Transformer

  Protein function

  The TAPE Transformer learns contextual protein representations using masked-residue pretraining and a task-specific prediction head.

This index reflects a dated catalogue, not an exhaustive census. Source checking does not mean independent reproduction; compare results only under compatible protocols, datasets and metrics.