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SettingsResearch demo · not for clinical or commercial use
Corollary
  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
300
Datasets
248
Organisations
131

Labs, institutes and companies

Ready to run
21

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

286 entries in Biology

Showing 48 of 286

Ready to run

17
InstantModel

AlphaFold DB Lookup

DeepMind / EMBL-EBI

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

structure retrieval
InstantModel

ESMFold

Meta AI (FAIR)

Single-sequence folding in seconds — 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

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

Everything else indexed

31
AbLang2Oxford Protein Informatics GroupAntibody-specific language model trained on the Observed Antibody Space.sequence embeddingOn 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
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.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
ESMC 300Mbiohub300M-parameter ESMC protein language model — compact variant of the ESMC family for protein-embedding workflows, fits on a single consumer GPU.sequence embeddingOn demand
ESMC 600Mbiohub600M-parameter ESMC protein language model — provides digital representations of proteins for therapeutic engineering, variant-effect prediction, and transfer learning across protein tasks.sequence embeddingOn demand
ESMC 6BbiohubFlagship 6B-parameter ESMC protein language model — state-of-the-art protein embeddings for variant-effect prediction, protein engineering, and biology research, trained on billions of protein sequences.sequence embeddingOn 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.structure predictionOn demand
ESMFold2-ExperimentalbiohubExperimental ESMFold2 variant exploring new training recipes and architectural changes for protein structure prediction, design, and confidence estimation.structure predictionOn demand
ESMFold2-Experimental-FastbiohubFast variant of the experimental ESMFold2 line — combines accelerated inference with the research-recipe improvements of the experimental branch.structure predictionOn demand
ESMFold2-FastbiohubAccelerated variant of ESMFold2 — optimised for high-throughput structure prediction across large protein sets while retaining strong accuracy.structure predictionOn 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
MAMMALIBM ResearchTask-specific predictions for binding affinity, blood–brain barrier permeability, and protein solubility.multi taskOn demand
MAMMAL solubilityIBM ResearchBinary protein-solubility classification from amino-acid sequence.protein solubilityOn demand
MIST 1.8B · ⟨R²⟩mist-modelsMIST 1.8B fine-tuned for electronic spatial extent from QM9.feature-extractionOn demand
MIST 1.8B · BACEmist-modelsMIST 1.8B fine-tuned on BACE — Alzheimer-target inhibition classification.feature-extractionOn demand
MIST 1.8B · BBBPmist-modelsMIST 1.8B fine-tuned on BBBP — blood-brain-barrier permeability.feature-extractionOn demand
MIST 1.8B · ClinToxmist-modelsMIST 1.8B fine-tuned on ClinTox — clinical toxicity classification.feature-extractionOn demand
MIST 1.8B · Cvmist-modelsMIST 1.8B fine-tuned for heat capacity Cv from QM9.feature-extractionOn demand

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