Biological networks for data analysis, integration and visualization
Biological networks such as protein-protein interaction networks or gene regulatory networks are an integral part to understand biological systems. We use such networks to interpret and integrate large-scale data coming from expression studies. We have developed several algorithms for network analysis and visualization:
1) miMerge and miScore for the generation of non-redundant protein interaction networks (Villaveces, et al., Database, 2015, doi: 10.1093/database/bau131)
2) KEGGViewer (Villaveces, et al., F1000Res 3:43, 2014, doi: 10.12688/f1000research.3-43.v1) for the visualization and integration of pathway data; and PsiquicGraph (Villaveces, et al., F1000Res 3:44, 2014, doi: 10.12688/f1000research.3-44.v1) both available via the BioJS platform;
3) the Cytoscape plugins viPEr for generating focus networks based on -omics data and PEANUT for pathway enrichment of focus networks (Garmhausen et al., BMC Genomics 16:790, 2015, doi: 10.1186/s12864-015-2017-z).
viPEr-networks of Statin-treated human hepatocytes. (A) Focus network of all differentially regulated genes upon Atorvastatin treatement and direct Atorvastatin targets. (B) Focus networks based on same data between the Transcription Factors FoxA1/A2/A3 and all the main Atorvastatin target, HMGCR.
This project was funded by the BMBF grants 'HEPATOSYS' and 'SYBACOL'. and the Max Planck Society.