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  1. Catalog

Library

Find the model or dataset for the question you have.

Ask in plain language and we will work out where the answer lives — or filter the index yourself. Almost everything here runs on our servers, from this page, with no setup.

Models
297
Datasets
245
Organisations
128

Labs, institutes and companies

Ready to run
24

Including 6 that run free and instantly

Looking for a particular value, not a particular dataset?Search schemas, rows and column statistics inside the data itself.

Things that work

Filtering

277 entries in Biology

Showing 48 of 277

Ready to run

19
InstantModel

AlphaFold DB Lookup

DeepMind / EMBL-EBI

Fetch a pre-computed structure for any UniProt accession — 247M entries, instantly.

structure retrieval
InstantModel

ESMFold2

EvolutionaryScale / CZ Biohub

Single-sequence folding at state-of-the-art accuracy — no MSA, no waiting.

structure prediction
InstantModel

PDB Structure Fetch

RCSB Protein Data Bank

Experimentally determined coordinates and metadata for any PDB entry.

structure retrieval
InstantModel

Sequence Analytics

Corollary Labs

Composition, molecular weight, isoelectric point and hydropathy — deterministic.

annotation
ReadyModel

AlphaFold2

DeepMind (served as BioNeMo NIM)

The reference MSA-based predictor, with managed MSA search included.

structure prediction
ReadyModel

BioMedGPT-R1

PharMolix / OpenBioMed

Reasoning-capable biomedical LLM with chain-of-thought over molecules.

chat
ReadyModel

Boltz-2

MIT × Recursion

Structure and binding affinity in one pass, approaching FEP accuracy 1000× faster.

structure prediction
ReadyModel

DiffDock

MIT / Barzilay Lab

Diffusion docking: 38% top-1 success versus 23% for classical AutoDock.

molecular docking
ReadyModel

DNABERT-2

Zhou et al., Northwestern

BPE-tokenised genomic BERT for motif, splice site and regulatory classification.

motif discovery
ReadyModel

ESM2-3B

Meta FAIR

High-quality 1,280-dimensional protein embeddings for everything downstream.

sequence embedding
ReadyModel

ESM2-650M

Meta FAIR

The throughput workhorse of the ESM2 family — good embeddings, tiny footprint.

sequence embedding
ReadyModel

Evo 2

Arc Institute / Stanford

Genome-scale foundation model spanning nucleotide to whole-genome context.

sequence generation
ReadyModel

Galactica

Meta AI

Scientific LLM retained as a domain-knowledge evaluation baseline only.

evaluation baseline
ReadyModel

MAMMAL

IBM Research

One model across proteins, molecules and omics — SOTA on 9 of 11 discovery tasks.

multi task
ReadyModel

Nucleotide Transformer v2

InstaDeep / Wellcome Sanger

DNA foundation model for regulatory elements, promoters and variant scoring.

regulatory prediction
ReadyModel

ProGen2

Salesforce Research

Autoregressive protein generation up to 6.4B parameters, with an antibody variant.

sequence generation
ReadyModel

ProteinMPNN

Baker Lab

Inverse folding: given a backbone, design sequences that actually fold onto it.

inverse folding
ReadyModel

RFDiffusion

Baker Lab / Institute for Protein Design

De novo backbone generation by denoising diffusion — the binder-design workhorse.

backbone generation
ReadyModel

TxGemma-27B

Google Health AI

Open therapeutics LLM covering 66 Therapeutic Data Commons tasks.

chat

Everything else indexed

29
AbLang2Oxford Protein Informatics GroupAntibody-specific language model trained on the Observed Antibody Space.sequence embeddingOn demand
ABMIL (CONCH v1.5 features, pc108-24k)MahmoodLabAttention-based MIL classifier on CONCH v1.5 features — pan-cancer pc108-24k training for slide-level subtyping and downstream pathology evaluation.image-feature-extractionOn demand
ABMIL (UNI features, pc108-24k)MahmoodLabAttention-based MIL classifier on UNI features — pan-cancer pc108-24k training; provides slide-level aggregation over the original UNI patch encoder.image-feature-extractionOn demand
ABMIL (UNI2 features, pc108-24k)MahmoodLabAttention-based multiple-instance learning classifier on UNI2 features — pan-cancer pc108-24k training; pairs with the UNI2-h patch encoder for slide-level inference.image-feature-extractionOn demand
AIFS Single 1.0ecmwfFirst 1.0 release of the deterministic AIFS — graph-based global weather forecasting model from ECMWF on the Anemoi framework.forecastingOn demand
ANARCIOxford Protein Informatics GroupAntibody numbering and region annotation — Chothia, IMGT, Kabat.annotationOn demand
AntiFoldHummer et al., DTUInverse folding specialised for antibody backbones and CDR loops.inverse foldingOn demand
AutoDock VinaScripps ResearchThe docking engine every other docking paper compares itself against.molecular dockingOn demand
BioCLIP 2imageomicsOpenCLIP-based foundation model for organismal biology — zero-shot species classification from photographs across the tree of life, trained on TreeOfLife-200M.zero-shot-image-classificationOn demand
Chai-1Chai DiscoveryOpen multimodal complex prediction across proteins, nucleic acids and ligands.complex predictionOn demand
CONCHMahmoodLabContrastive vision-language model for pathology trained on 1.17M histology image–caption pairs — enables zero-shot classification, retrieval, and report-grounded analysis on H&E whole-slide images.image-feature-extractionOn demand
CONCH v1.5MahmoodLabUpdated CONCH checkpoint (v1.5) with strengthened image-side encoder and expanded pretraining corpus — drop-in upgrade for zero-shot and few-shot pathology tasks.image-feature-extractionOn demand
DoctoBERT-fr-basedoctolib-labFrench medical encoder (RoBERTa, 111M params, 512-token context) pretrained from scratch on FineMed-fr — state-of-the-art on DrBenchmark, leading five of seven tasks across French and English medical encoder families.fill-maskOn demand
DoctoModernBERT-fr-basedoctolib-labFrench medical encoder (ModernBERT, 149M params, up to 8,192-token context) pretrained from scratch on FineMed-fr — best on real-world clinical NER and top-ranked on DrBenchmark. ## Blog Posts (18)fill-maskOn demand
EnformerDeepMindSequence-to-expression across a 200kb window covering distal enhancers.expression predictionOn demand
ESM-IF1Meta FAIRLanguage-model-informed inverse folding — an alternative view to ProteinMPNN.inverse foldingOn demand
ESM3EvolutionaryScaleSequence, structure and function unified in one generative transformer.generationOn demand
ESMFold2biohubState-of-the-art protein structure prediction and design model — defines a new frontier for speed and accuracy, with unprecedented success rates for protein binder and antibody generation.feature-extractionOn demand
ESMFold2-ExperimentalbiohubExperimental ESMFold2 variant exploring new training recipes and architectural changes for protein structure prediction, design, and confidence estimation.feature-extractionOn demand
ESMFold2-Experimental-FastbiohubFast variant of the experimental ESMFold2 line — combines accelerated inference with the research-recipe improvements of the experimental branch.feature-extractionOn demand
ESMFold2-FastbiohubAccelerated variant of ESMFold2 — optimised for high-throughput structure prediction across large protein sets while retaining strong accuracy.feature-extractionOn demand
eva-rnaScientaLabTransformer foundation model producing sample-level and gene-level embeddings from RNA-seq profiles (bulk, microarray, pseudobulked single-cell) in human and mouse.feature-extractionOn demand
FlashPPItattabioFast protein-protein interaction prediction model — trained for high-throughput screening of interaction networks.feature-extractionOn demand
GENA-LM BERT base (T2T)AIRI-InstituteBERT-base-style genomic foundation model trained on T2T assemblies — lighter-weight backbone for genomic sequence understanding.fill-maskOn demand
GENA-LM BERT large (T2T)AIRI-InstituteBERT-large-style genomic foundation model trained on telomere-to-telomere human assemblies — supports variant interpretation, regulatory prediction, and downstream genomic tasks.fill-maskOn demand
gLM2 650Mtattabio650M-parameter genomic foundation model from Tatta Bio — trained on the OMG open-mixed-genomes corpus for sequence-level biological reasoning.fill-maskOn demand
ImmuneBuilderOxford Protein Informatics GroupSub-second structure prediction for antibodies, nanobodies and TCRs.structure predictionOn demand
Indus SDE v0.2nasa-impactScience domain extraction model for identifying and classifying scientific concepts, variables, and entities from geoscience and atmospheric science text.fill-maskOn demand
IsoformerInstaDeepAITransformer model integrating DNA sequence, RNA expression, and protein context for isoform-level gene expression prediction.fill-maskOn demand

229 more behind this view