Molecular Biology Graph Visualisation and Analysis Tool
Biogranat Development Team1,2
1 University of Applied Sciences and Arts Hannover, Faculty IV, Department of Computer Science, Ricklinger Stadtweg 120, 30459 Hannover, Germany
2 King's College London, Department of Medical and Molecular Genetics, 8th floor Guy's Hospital Tower Wing, London SE1 9RT, United Kingdom
BioGranat is a molecular biology graph visualisation and analysis tool developed in collaboration by Hochschule Hannover and King's College London. It is based on the Java OSGi bundle architecture and currently provides a graphical user interface, input and output routines for various graph file formats, a facility to use the JUNG library, 2D graph layout routines, 3D visualisation of graphs, JAVA scripting and graph analysis algorithms. Further developments address graphics export (jpeg, vector formats), generation of random graphs and the import of biological meta-information. Biogranat can be used to integrate and analyse large-scale gene networks. BioGranat is available as Open Source Software.
BioGranat is available via sourceforge.
We would like to acknowledge funding from the German Academic Exchange Service (DAAD PPP D/07/09921), the British Council (ARC1297) and the Royal Society (RG100252).
Lehne B, Barkas N, Dand N, Sutherland R, Tebbe C, Sprengel F, Ahlers V and Schlitt T
De-novo discovery of disease associated subnetworks using Region Growing Analysis
Dand N, Sprengel F, Ahlers V, Schlitt T
BioGranat-IG: A network analysis tool to suggest mechanisms of genetic heterogeneity from exome sequencing data
Mendig A, Sprengel F, Schlitt T, Ahlers V
GPU-beschleunigtes 3D-Layout komplexer Netzwerke
[GPU-accelerated 3D-Layout of complex networks]
published in Go-3D 2009: Go for Innovations; Editors von Lukas U, Mahnke EM, Vahl M
Fraunhofer-Verlag, Stuttgart, 2009
BioGranat-RGA has been developed to find the largest subnetwork that contains as many as possible genes from a given ranked list of genes. This ranked list can for example be derived from GWAS results using methods published by Lehne et al. in PLoS ONE. 2011, 6(6): e20133.
BioGranat-IG used for finding the smallest subnetwork that represents all or most individuals; the input data is usually a biological network and lists of genes carrying sequence variants in indivduals whose exomes have been sequenced.
Region Growing Analysis
|application||"oligo"-genic disease||complex disease|
|typical data||exome sequences||GWAS|
ranked gene list
|BioGranat Screenshot. BioGranat is available via sourceforge.|