The BioNet package provides an extensive framework for integrated network analysis using R and BioConductor. It includes the statistics for the integration of transcriptomic and functional data with biological networks, the methods for scoring of nodes, methods for optimal, suboptimal and fast heuristic searches, as well as routines for the visualization of the fitted model and resulting modules.
Keywords for this software
References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
- Song, Wei; Liu, Huaping; Wang, Jiajia; Kong, Yan; Yin, Xia; Zang, Weidong: MATHT: a web server for comprehensive transcriptome data analysis (2018)
- von Stechow, Louise (ed.); Delgado, Alberto Santos (ed.): Computational cell biology. Methods and protocols (2018)
- Álvarez-Miranda, Eduardo; Sinnl, Markus: A relax-and-cut framework for large-scale maximum weight connected subgraph problems (2017)
- Fröhlich, Holger: Including network knowledge into Cox regression models for biomarker signature discovery (2014)
- Beisser, Daniela; Klau, Gunnar W.; Dandekar, Thomas; Müller, Tobias; Dittrich, Marcus T.: Bionet: an R-package for the functional analysis of biological networks (2010) ioport