Descripción del proyecto
De las representaciones secuenciales a las gráficas: un cambio de paradigma en la genómica
La secuenciación del genoma busca determinar el orden de As, Cs, Gs y Ts, representando los nucleótidos de ADN en el genoma de un organismo. Los progresos correspondientes han dado lugar a cantidades cada vez mayores de datos en todo el mundo. En el proyecto ALPACA, financiado en el marco de las Acciones Marie Skłodowska-Curie, se desarrollarán representaciones gráficas de genomas basadas en la combinación de la variación individual de manera evolutivamente significativa, lo que permitirá procesar y analizar los datos de secuenciación de manera más eficiente que los métodos tradicionales, basados en representaciones ordinarias del genoma de tipo secuencia. El cambio de paradigma desempeñará un papel fundamental en la medicina personalizada y el análisis de patógenos.
Objetivo
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.
Ámbito científico
Programa(s)
Régimen de financiación
MSCA-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)Coordinador
33615 Bielefeld
Alemania