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Computational Biology

The cost of genome sequencing is decreasing rapidly owing to recent advances in next-generation sequencing technologies. As a consequence, vast amount of genomic and transcriptomic data are accumulating, and existing analysis tools are struggling to handle such big multi-omics datasets.

CaSToRC Computational Biology group aims to partner with biologists and bioinformaticians to provide effective tools and analyses to facilitate visualisation and understanding of biological data.


The NinjaViewer: a versatile visualisation platform for functional and evolutionary analysis of multi-omics data

NinjaViewer is an interactive web-based data analysis and visualisation platform specifically designed to integrate several types of biological data, including phylogenetic relationship, gene, protein, pathway, genetic variation, genotype-phenotype association and literature knowledge, into a coherent interlinked and comprehensible display. The platform serves information in an intuitive and interactive manner to facilitate biological data analysis.

In its current form, NinjaViewer enables visual analysis and cross referencing of genomic and transcriptomic data from 21 anopheline and 7 Plasmodium species. It enables concurrent display and dynamic annotation of all protein-coding genes and orthologous gene groups integrated with gene expression and orthology data. The platform is readily extendible towards other species, and it can incorporate information from related datasets, such as population data.

computational biology ninja viewer
Figure 1 Screenshot of a typical NinjaViewer session with concurrent displays of orthology and expression maps overlaid with functional and evolutionary information


Key Partners

Imperial College London (UK)

CyI People

K. Erguler, G. K. Christophides

Conference Proceedings

NinjaViewer: functional and evolutionary analysis of multi-omics data.
Erguler K, MacCallum RM, Kirmitzoglou I, Ho N, Brockman A, Koukos P, Chan T, Waterhouse R, Christophides GK.
3rd EMBO Conference on Visualizing Biological Data (VIZBI 2016). March 9–11, 2016.