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alphafoldfetch

imported

software/alphafoldfetch

CLI for downloading AlphaFold structures using UniProt IDs or FASTA files

Machine-generated from the listed sources and not yet reviewed by a human.

record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
active
Maturity
deployed
Organization
unknown
Country
unknown
Documentation
unknown
Tags
ai · alphafold · bioinformatics · computational-biology · ml · proteomics
Regulatory
unknown
built by · 2

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • protspacealphafold · bioinformatics · computational-biology

    Explore protein language model embeddings in your browser — surface relationships sequence similarity misses, overlay annotations, and transfer labels (EAT). Nothing uploaded.

  • PHIStructalphafold · bioinformatics

    Published in Bioinformatics. Phage-host interaction prediction tool that incorporates protein structure information in representing receptor-binding proteins (RBPs). It improves performance…

  • PyFeatbioinformatics · computational-biology · proteomics

    A Python-based Effective Feature Generation Tool from DNA, RNA, and Protein Sequences

  • PyFeat-2.xbioinformatics · computational-biology · proteomics

    Biological Feature Representation Tool form the Sequences

  • redunbioinformatics · ml

    Yet another redundant workflow engine

  • ggetalphafold

    🧬 gget enables efficient querying of genomic reference databases

sources
  1. api.github.com/repos/mansanlab/alphafoldfetch
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-05-11, 12 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/0.json→ .entries["alphafoldfetch"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.