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BioNet

Bioc current

Routines for the functional analysis of biological networks

v1.72.0 · software · GPL (>= 2)

Release Lineage

Entered 2.7 · Oct 18, 2010

Current · Requires R 4.6

1.0 In 32 of 49 releases 3.23

Description

This package provides functions for the integrated analysis of protein-protein interaction networks and the detection of functional modules. Different datasets can be integrated into the network by assigning p-values of statistical tests to the nodes of the network. E.g. p-values obtained from the differential expression of the genes from an Affymetrix array are assigned to the nodes of the network. By fitting a beta-uniform mixture model and calculating scores from the p-values, overall scores of network regions can be calculated and an integer linear programming algorithm identifies the maximum scoring subnetwork.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

63 42 exported

Complexity

5.1 avg / 30 max

Call network

63 nodes / 43 edges

Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.

Loading call graph…

Lowest coverage

Per-function coverage is not measured for this package yet.

Code

Structure

Lines of code

4,792

Files

73

Compiled share

0%

Has compiled src

No

Language breakdown

R 2,104 (43.9%)Docs 1,539 (32.1%)Vignettes 1,149 (24%)

API

Exported functions

42

Internal functions

21

Testing & CI

Has tests

No

Test-to-code ratio

0.00

testthat edition

CI present

No

CI type

[]

PR gated

No

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

0%

Unsafe pattern score

0

Dep constraint coverage

20%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

2.10.0

System requirements

C++ standard

License

GPL (>= 2)

License flags

SPDX valid, OSI approved

History

Versions

32

First release

2010-10-18

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

Dep drift

5

LOC over versions

v2.7: 3,307 LOCv2.8: 3,350 LOCv2.9: 3,350 LOCv2.10: 3,657 LOCv2.11: 3,657 LOCv2.12: 3,657 LOCv2.13: 3,636 LOCv2.14: 4,311 LOCv3.0: 4,311 LOCv3.1: 4,322 LOCv3.2: 4,322 LOCv3.3: 4,322 LOCv3.4: 4,322 LOCv3.5: 4,322 LOCv3.6: 4,322 LOCv3.7: 4,322 LOCv3.8: 4,322 LOCv3.9: 4,322 LOCv3.10: 4,322 LOCv3.11: 4,322 LOCv3.12: 4,792 LOCv3.13: 4,792 LOCv3.14: 4,792 LOCv3.15: 4,792 LOCv3.16: 4,792 LOCv3.17: 4,792 LOCv3.18: 4,792 LOCv3.19: 4,792 LOCv3.20: 4,792 LOCv3.21: 4,792 LOCv3.22: 4,792 LOCv3.23: 4,792 LOC

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
95%
Documented parameters
99%
Return-value docs
67%
References docs
16%

Topics

Depended on by (5)

Bioconductor (4)

CRAN (1)

People

Marcus Dittrich

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("BioNet")

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for BioNet version 1.72.0 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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