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IM2Deep

imported

software/im2deep

Collisional cross-section prediction for modified and multiconformational peptides

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

record
Category
Software & Systems
Subcategory
unknown
License
Apache-2.0(osi)
Status
active
Maturity
deployed
Organization
CompOmics
Country
unknown
Documentation
unknown
Tags
collisional-cross-section · ion-mobility · mass-spectrometry · peptides · proteomics · timstof
Regulatory
unknown
built by · 3

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.

  • ionmobcollisional-cross-section · ion-mobility · mass-spectrometry · proteomics

    An open-source prediction framework for peptide ion collision cross section (CCS) values with python.

  • dlomixmass-spectrometry · peptides · proteomics

    Python framework for Deep Learning in Proteomics

  • peptacularmass-spectrometry · peptides · proteomics

    A Python package for peptide sequence analysis built around ProForma 2.1 notation. Calculate masses, generate fragments, predict isotopic patterns, and more.

  • DeepLCpeptides · proteomics

    DeepLC: Retention time prediction for peptides carrying any modification.

  • DeepRTpluspeptides · proteomics

    Deep (Transfer) Learning for Peptide Retention Time Prediction

  • PROSPECTmass-spectrometry · peptides

    Proteomics Mass Spectrometry Datasets for Machine Learning

sources
  1. api.github.com/repos/CompOmics/IM2Deep
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-07-16, 14 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/53.json→ .entries["im2deep"]

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