cdnormbio
importedsoftware/cdnormbio
R package: Condition-Decomposition Normalization for Biological Applications
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/carlosproca/cdnormbio
- Documentation
- unknown
- Tags
- bioinformatics · biological-data-analysis · biostatistics · high-throughput · normalization
- Regulatory
- unknown
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.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- GCModellerbioinformatics · biological-data-analysis
GCModeller: genomics CAD(Computer Assistant Design) Modeller system in .NET language
- phigarobioinformatics · biological-data-analysis
Phigaro is a scalable command-line tool for predicting phages and prophages
- photonbioinformatics · biological-data-analysis
PHOsphoproteomic dissecTiOn using Networks
- py3plexbioinformatics · biological-data-analysis
Py3plex - A multilayer complex network visualization and analysis library in python3
- LiberTEM/LiberTEM: 0.16.0high-throughput
Homepage: https://libertem.github.io/LiberTEM/ GitHub repository: https://github.com/LiberTEM/LiberTEM/ PyPI: https://pypi.org/project/libertem/ LiberTEM is an open source platform for…
- rustimshigh-throughput
A Framework for IMS-MS Raw Data Processing written in Rust and Python.
- api.github.com/repos/carlosproca/cdnormbioretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2017-03-08, 4 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 →
/v1/entries/50.json→ .entries["cdnormbio"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.