ABSTRACT
OBJECTIVE: We have created an open-source application and framework for rapid GPU-accelerated prototyping, targeting image analysis, including volumetric images such as CT or MRI data. METHODS: A visual graph editor enables the design of processing pipelines without programming. Run-time compiled compute shaders enable prototyping of complex operations in a matter of minutes. RESULTS: GPU-acceleration increases processing the speed by at least an order of magnitude when compared to traditional multithreaded CPU-based implementations, while offering the flexibility of scripted implementations. CONCLUSION: Our framework enables real-time, intuition-guided accelerated algorithm and method development, supported by built-in scriptable visualization. SIGNIFICANCE: This is, to our knowledge, the first tool for medical data analysis that provides both high performance and rapid prototyping. As such, it has the potential to act as a force multiplier for further research, enabling handling of high-resolution datasets while providing quasi-instant feedback and visualization of results.
ABSTRACT
MOTIVATION: In the systems biology era, high-throughput omics technologies have enabled the unraveling of the interplay of some biological entities on a large scale (e.g. genes, proteins, metabolites or RNAs). Huge biological networks have emerged, where nodes correspond to these entities and edges between them model their relations. Protein-protein interaction networks, for instance, show the physical interactions of proteins in an organism. The comparison of such networks promises additional insights into protein and cell function as well as knowledge-transfer across species. Several computational approaches have been developed previously to solve the network alignment (NA) problem, but only a few concentrate on the usability of the implemented tools for the evaluation of protein-protein interactions by the end users (biologists and medical researchers). RESULTS: We have created CytoGEDEVO, a Cytoscape app for visual and user-assisted NA. It extends the previous GEDEVO methodology for global pairwise NAs with new graphical and functional features. Our main focus was on the usability, even by non-programmers and the interpretability of the NA results with Cytoscape. AVAILABILITY AND IMPLEMENTATION: CytoGEDEVO is publicly available from the Cytoscape app store at http://apps.cytoscape.org/apps/cytogedevo In addition, we provide stand-alone command line executables, source code, documentation and step-by-step user instructions at http://cytogedevo.compbio.sdu.dk CONTACT: malek@tugraz.at SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
