Projektbeschreibung
Von sequenz- zu graphenbasierten Darstellungen – ein Paradigmenwechsel in der Genomik
Bei der Genomsequenzierung geht es darum, die Reihenfolge von As, Cs, Gs und Ts zu bestimmen, die die DNA-Nukleotide im Erbgut eines Organismus repräsentieren. Fortschritte in diesem Forschungsbereich haben weltweit zu einer stetig wachsenden Datenmenge geführt. Das im Rahmen der Marie-Skłodowska-Curie-Maßnahmen finanzierte Projekt ALPACA wird graphenbasierte Darstellungen für Genome entwickeln, die auf evolutionär bedeutsame Weise auf der Kombination einzelner Variationen aufbauen. Das ermöglicht eine effizientere Verarbeitung und Analyse der Daten im Vergleich zu herkömmlichen Ansätzen, die auf gewöhnlichen sequenzartigen Genomdarstellungen beruhen. Dieser Paradigmenwechsel wird eine wichtige Rolle in der personalisierten Medizin und Pathogenanalyse spielen.
Ziel
Genomes are strings over the letters A,C,G,T, which represent nucleotides, the building blocks of DNA. In view of ultra-large amounts of genome sequence data emerging from ever more and technologically rapidly advancing genome sequencing devices—in the meantime, amounts of sequencing data accrued are reaching into the exabyte scale—the driving, urgent question is: how can we arrange and analyze these data masses in a formally rigorous, computationally efficient and biomedically rewarding manner?
Graph based data structures have been pointed out to have disruptive benefits over traditional sequence based structures when representing pan-genomes, sufficiently large, evolutionarily coherent collections of genomes. This idea has its immediate justification in the laws of genetics: evolutionarily closely related genomes vary only in relatively little amounts of letters, while sharing the majority of their sequence content. Graph-based pan-genome representations that allow to remove redundancies without having to discard individual differences, make utmost sense. In this project, we will put this shift of paradigms—from sequence to graph based representations of genomes—into full effect. As a result, we can expect a wealth of practically relevant advantages, among which arrangement, analysis, compression, integration and exploitation of genome data are the most fundamental points. In addition, we will also open up a significant source of inspiration for computer science itself.
For realizing our goals, our network will (i) decisively strengthen and form new ties in the emerging community of computational pan-genomics, (ii) perform research on all relevant frontiers, aiming at significant computational advances at the level of important breakthroughs, and (iii) boost relevant knowledge exchange between academia and industry. Last but not least, in doing so, we will train a new, “paradigm-shift-aware” generation of computational genomics researchers.
Wissenschaftliches Gebiet
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MSCA-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)Koordinator
33615 Bielefeld
Deutschland