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BayesENproteomics

imported

software/bayesenproteomics

Non-linear Bayesian elastic net regression for calculating protein and PTM fold changes from peptide intensities in label-free, bottom-up proteomics on heterogeneous primary human samples.

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

BayesENproteomics project image
GitHub preview card for VenkMallikarjun/BayesENproteomics. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Repository
github.com/VenkMallikarjun/BayesENproteomics
Documentation
unknown
Tags
matlab · post-translational-modification · proteomics
Regulatory
unknown
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.

  • BENPPypost-translational-modification · proteomics

    Python implementation of BayesENproteomics with user-customised models and other additional features

  • MSstatsPTMpost-translational-modification · proteomics

    Post Translational Modification (PTM) Significance Analysis in shotgun mass spectrometry-based proteomic experiments

  • PTMVisionpost-translational-modification · proteomics

    Web application for the interactive visualization and exploration of post-translational modifications of proteins from open and closed search software.

  • pyAscorepost-translational-modification · proteomics

    A python package for fast post translational modification localization, powered by Cython.

  • psi-mod-CVpost-translational-modification · proteomics

    PSI-MOD ontology for modified and unmodified amino acid residues

  • artMSpost-translational-modification

    Analytical R Tools for Mass Spectrometry

sources
  1. api.github.com/repos/VenkMallikarjun/BayesENproteomics
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2019-09-11, 3 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/33.json→ .entries["bayesenproteomics"]

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