Exploring Mycosphaerella graminicola and Fusarium graminearum sequence homology network (Source: Artem Lysenko)
All-versus-all BLAST results as visulaised in Ondex frontend. The nodes are proteins of Mycosphaerella graminicola and Fusarium graminearum, edges are bidirectional BLAST hits. The colour and thickness of the edge shows the normalized similarity scores (negative average log of e-values of the two hits). Combined with the annotation from Phi-base database this network was used to facilitate exploration of virulence assosiated genes across these two species. The interactive plot in the lower left shows the distribution of the BLAST scores and serves as an interface for threshold filtering of the graph.
Qualitative modelling of nitrogen uptake regulation in Arabidopsis
Protein-protein interaction (PPI) data from the TAIR curated PPI and IntAct can be combined with the co-expression data from the ATTEDII database using Ondex. Positive co-expression by itself does not appear to be a strong indicator of interaction. However, it is a good indicator of interacting proteins that are in the same complex. In the graph below, these are clusters of nodes where all of them interact with each other. Some of these clusters also have positively correlated expression between all members.
The colour-coded annotation used here shows how influential some concepts proteins in this case are within the network. The colour legend is based on the rainbow scale, where purple is low and red is high.
Arabidopsis Meta-coexpression network for genes differentially expressed under low nitorgen in nar2.1 mutant (Source: Artem Lysenko)
Nodes represent genes and edges - coexpression relationships. The transcription factors are labeld and highlighted in purple, their direct neighbourhood highlighted in blue. The annotation highlighted a module almost exculsively consisting of transcription factors (lower-right). Further analysis revealed that it is also present in experiments looking at responce to ethylene phytoyhormone, and therefore may be of interest for understanding previously observed link between responce to ethyle, nitrogen uptake and NAR2.1 gene.
Context of changes in gene expression with pathways (Source: Matthew Hindle)
An Ondex pipeline was developed for analysis of time-course microarray data on drought stress in three cultivars of durum wheat. Ondex was used to integrate databases that contained metabolic pathways and functional protein annotations in plant model organisms and closely related species to wheat. Sequence alignment tools, which are closely integrated into Ondex, were used to identify putative functional orthologs to genes on the Affymetrix microarray chip. A combination of statistical analysis and graph visualization techniques in the Ondex Visualization Toolkit (OVTK) was used to dissect the temporal changes in gene and pathway regulation.
An alternative visualisation of the analysis of time-course microarray data on drought stress in three cultivars of durum wheat. This representation shows the enzymes significantly up/down regulated within the Jasmonic acid biosynthesis pathway after two days of stress on one of the cultivars. Blue squares represent ortholog proteins, blue circles reactions and pink squares pathways. Squares are target sequences, their size is proportional to expression and their colour depends on regulation since the pre-stress point zero. Red shows up regulation, green down, while yellow means the regulation was not significant. Black nodes indicate that the target sequence was not significantly expressed in any time point.
Ondex Chemogenomics (Source: Jan Taubert)
New features in Ondex can be used to display chemical structure diagrams as node glyphs. This screenshot shows a fragment of a biochemical pathway with metabolite nodes displayed as chemical structures.
An alternative visualisation feature allows quantitative data from a time course of biological activity to be displayed as a node glyph.
More screenshots available HERE