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AI Drug Discovery · Molecular Property Prediction

Uni-Mol

By DeepModeling / Uni-Mol contributors →

Learning molecular representations from three-dimensional conformations

Learning molecular representations from three-dimensional conformations. The repository contains several related models; select a documented release and evaluate domain shift.

Learning molecular representations from three-dimensional conformationsInput: Molecular structures, conformers and task labelsOutput: Molecular embeddings and task-specific predictions
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Overview

Learning molecular representations from three-dimensional conformations. The repository contains several related models; select a documented release and evaluate domain shift.

Information checked against an official source; not a hands-on test. Source · Last reviewed: 16/09/2026, 17:33:40

Key Features

  • Learning molecular representations from three-dimensional conformations
  • Input: Molecular structures, conformers and task labels
  • Output: Molecular embeddings and task-specific predictions
Interactive 3D Structure

Uni-Mol Predicted Complex

Streams real 3D atomic coordinates from RCSB Protein Data Bank
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pLDDT / B-Factor:
>90 Very high 70-90 Confident 50-70 Low <50 Very low

Academic Context & Research Evidence

Biological & Workflow Fit

Compute & Hardware
Consult linked installation guidance; workload dependent
Licensing & Academic Use
Review the linked release, model weights, datasets and service terms separately
Documented Evidence
Project or provider documentation; no local performance benchmark

Cite this Tool

Use this citation format when referencing Uni-Mol in scientific publications and benchmark papers.

@software{uni_mol_2026,
  title = {{Uni-Mol}},
  author = {{DeepModeling / Uni-Mol contributors}},
  year = {2026},
  url = {https://github.com/deepmodeling/Uni-Mol},
  note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}

Peer-Reviewed Literature & Preprints

Live scientific citations streamed from Europe PMC and PubMed for Uni-Mol.

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Technical / Product Information

Missing values mean the catalog has no recorded information. They do not mean a feature is absent.

Entry typeResearch software / model
Access modePublic code / project terms
AI roleScientific machine learning
Input dataMolecular structures, conformers and task labels
Output dataMolecular embeddings and task-specific predictions
Licence conditionsReview the linked release, model weights, datasets and service terms separately
Commercial eligibilityNot independently confirmed
Compute requirementsConsult linked installation guidance; workload dependent
ValidationEvaluate on representative data; no clinical suitability established
TypeNot recorded
Intended useBiological and pharmaceutical research
CompatibilityNot recorded
LimitationsThe repository contains several related models; select a documented release and evaluate domain shift.
Evidence levelProject or provider documentation; no local performance benchmark
AvailabilitySee project access and maintenance status
Price / accessSee project terms; compute costs may apply

Research fit & compatibility

No software–hardware integration has been verified for this entry yet. Explore documented research workflows.

Gallery & resources

No licensed product photograph recorded for Uni-Mol yet. Visit the official resource below for manufacturer imagery.

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FAQ

Where is this product available?

See project access and maintenance status

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Peer Reviews & Community Ratings

Feedback from researchers and computational biologists evaluating Uni-Mol.

5.0
★★★★★Based on 0 researcher evaluations
Biological Accuracy
4.8/5
Ease of Installation
4.3/5
Documentation & Code
4.6/5