Project

Pan-genome Graph Algorithms and Data Integration

Goal: Modern sequencing technology produces genome sequence data on a gigantic scale reaching into exabytes. The emerging urgent question is how these volumes of data could be arranged and analysed in a computationally efficient and biomedically meaningful manner. This EU-funded project is going to explore graph-based representation of large genome datasets and determine their advantages over traditional sequence-based presentation of pan-genomic data. Genomes that are volutionarily close vary only a little and graph-based pan-genomic representation allows to remove redundancies while highlighting important differences. The research is going to demonstrate the advantage of the shift to the new data representation approach using comparative analysis, compression, integration and exploitation of genome data as the fundamental points.

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Gianluca Della Vedova
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Modern sequencing technology produces genome sequence data on a gigantic scale reaching into exabytes. The emerging urgent question is how these volumes of data could be arranged and analysed in a computationally efficient and biomedically meaningful manner. This EU-funded project is going to explore graph-based representation of large genome datasets and determine their advantages over traditional sequence-based presentation of pan-genomic data. Genomes that are volutionarily close vary only a little and graph-based pan-genomic representation allows to remove redundancies while highlighting important differences. The research is going to demonstrate the advantage of the shift to the new data representation approach using comparative analysis, compression, integration and exploitation of genome data as the fundamental points.