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mmtf-proteomics

imported

software/mmtf-proteomics

Methods for mapping proteomics data on 3D protein structure.

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

mmtf-proteomics project image
GitHub preview card for sbl-sdsc/mmtf-proteomics. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
Apache-2.0(osi)
Status
dormant
Maturity
deployed
Organization
sbl-sdsc
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
binder · jupyter-notebook · protein-data-bank · proteomics · pyspark
Regulatory
unknown
built by · 1

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.

  • Enhancing-Reproducibilitybinder · jupyter-notebook

    Companion notebooks for our paper on reproducible statistics in bioimage analysis — runs in-browser via Binder

  • spm-notebooksbinder · jupyter-notebook

    SPM Notebooks

  • AWS_EMR_Pysparklingjupyter-notebook · pyspark

    Set Up Python environment on AWS EMR cluster with H2O Sparkling Water (Pysparling)

  • pypdbprotein-data-bank · proteomics

    A Python API for the RCSB Protein Data Bank (PDB)

  • sparkmsproteomics · pyspark

    Spark package to perform downstream analysis of big data proteomics

  • bopepbinder · proteomics

    Bayesian Optimization for protein design and mining

sources
  1. api.github.com/repos/sbl-sdsc/mmtf-proteomics
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2020-01-18, 15 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/49.json→ .entries["mmtf-proteomics"]

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