Methods › AlphaFold

AlphaFold

87 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

AlphaFold is a deep learning based algorithm for accurate protein structure prediction. AlphaFold incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm.

Description from: Highly accurate protein structure prediction with AlphaFold

Image credit: DeepMind

Source: Highly accurate protein structure prediction with AlphaFold

Papers archive 2025-07-28

30 shown of 87, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 55 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Protein Structure Prediction23
Prediction15
Drug Discovery14
Protein Design13
Protein Folding13
Deep Learning7
Drug Design6
Diversity4
Language Modelling4
Protein Language Model4
Language Modeling3
Molecular Docking3
Representation Learning3
Benchmarking2
Blind Docking2
Contrastive Learning2
Multiple Sequence Alignment2
Property Prediction2
Retrieval2
3D Molecule Generation1

Usage over time archive 2025-07-28

Papers per year tagged with AlphaFold: 2021 to 2025, peak 26 26 0 2021: 5 papers 2021 2022: 17 papers 2022 2023: 17 papers 2023 2024: 26 papers 2024 2025: 22 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (87 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

The archive places this method in no collection.

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