open sourceother

AlphaFold

Revolutionizing protein structure prediction.

Developed by DeepMind

Official Site
350MParams
YesAPI Available
stableStability
2.0Version
OpenAI LicenseLicense
TensorFlowFramework
YesRuns Locally
Real-World Applications
  • Drug discoveryOptimized Capability
  • Protein engineeringOptimized Capability
  • Genomic researchOptimized Capability
  • Biotechnology applicationsOptimized Capability
Implementation Example
Example Prompt
Predict the 3D structure of a given protein sequence.
Model Output
"3D coordinates of protein backbone and side chains."
Advantages
  • ✓ Utilizes a novel deep learning architecture for high accuracy in protein structure prediction.
  • ✓ Significantly reduces the time required to determine protein structures compared to traditional methods.
  • ✓ Provides insights into protein interactions that can help in designing new therapeutics.
Limitations
  • ✗ Requires substantial computational resources for execution and training.
  • ✗ Limited by the quality and availability of training data.
  • ✗ Not all protein structures can be accurately predicted due to inherent biological variability.
Model Intelligence & Architecture

Technical Documentation

AlphaFold leverages deep learning techniques to model protein folding, greatly enhancing our understanding of biological processes and drug discovery.

Technical Specification Sheet
Technical Details
Architecture
Attention-based Neural Network
Stability
stable
Framework
TensorFlow
Signup Required
No
API Available
Yes
Runs Locally
Yes
Release Date
2021-07-15

Best For

Researchers and developers in the fields of bioinformatics and drug design.

Alternatives

Rosetta, MODELLER, I-TASSER

Pricing Summary

Open-source access available via GitHub.

Compare With

AlphaFold vs RosettaAlphaFold vs MODELLERAlphaFold vs PaeAlphaFold vs I-TASSER

Explore Tags

#protein structure prediction

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