Tutorial on biological networks
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Microarray vs. RNA-Seq: a comparison for active subnetwork discovery
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
PRASE: PageRank-based Active Subnetwork Extraction
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
| Hi-index | 3.84 |
Motivation: Increasing quantity and quality of data in transcriptomics and interactomics create the need for integrative approaches to network analysis. Here, we present a comprehensive R-package for the analysis of biological networks including an exact and a heuristic approach to identify functional modules. Results: The BioNet package provides an extensive framework for integrated network analysis in R. This includes the statistics for the integration of transcriptomic and functional data with biological networks, the scoring of nodes as well as methods for network search and visualization. Availability: The BioNet package and a tutorial are available from http://bionet.bioapps.biozentrum.uni-wuerzburg.de Contact:marcus.dittrich@biozentrum.uni-wuerzburg.de; tobias.mueller@biozentrum.uni-wuerzburg.de