GENESTORY
Assembling genome history from gene stories: Phylogeny aware genome scale inference of ancestral traits and ancient environments
| Coordinatore | Office for Research Groups Attached to Universities and Other Institutions of the Hungarian Academy of Sciences
Organization address
city: Budapest contact info |
| Nazionalità Coordinatore | Hungary [HU] |
| Totale costo | 87˙500 € |
| EC contributo | 87˙500 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2013-CIG |
| Funding Scheme | MC-CIG |
| Anno di inizio | 2013 |
| Periodo (anno-mese-giorno) | 2013-07-01 - 2016-12-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
Office for Research Groups Attached to Universities and Other Institutions of the Hungarian Academy of Sciences
Organization address
city: Budapest contact info |
HU (Budapest) | coordinator | 87˙500.00 |
Mappa
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Obiettivo del progetto (Objective)
'Using genomic data to understand how system-level traits of living organisms have been shaped by past environments and to disclose information on ancient environments and diversity are key issues of contemporary biology. Genome sequences that encode the complex networks underlying modern life and concealing the vast intricate record of the evolutionary history of their carriers are available. Modeling genome evolution, however, is complicated by fragmented histories, as the sequence of each gene is a result of a unique series of speciations, duplications, transfers and losses.
Here we propose to combine genome scale reconstruction of ancestral gene repertoires with system-level models of phenotype and models of ancient environment and diversity. The GENESTORY project will bring together probabilistic genome evolution methods developed by the researcher with the network theory and biophysical expertise of the host. Metabolic networks reconstructed from ancestral gene repertoires will be used to infer past environments and reconstructed duplication, transfer and loss events will be used to study the evolution of network architecture. Aside of the application of existing methods, leading a junior research group cofunded with the host, the researcher will pursue the development of new models of genome evolution and attempt to carry out in vitro validation of predicted gene interactions.
The project will result in a better understanding of genome evolution and the history of life on Earth, and provide new models for inferring the evolutionary history of genomes, species and complex phenotypes across billions of years of evolutionary time.'