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High Performance, Cloud and Symbolic Computing in Big-Data problems applied to mathematical modeling of Comparative Genomics

High Performance, Cloud and Symbolic Computing in Big-Data problems applied to mathematical modeling of Comparative Genomics

Objective

Large scale genomics projects exploiting high throughput leading technology have produced and continue to produce massive data sets with exponential growing rates. So far, only a small part of this data can be abstracted, managed and processed, giving an incomplete understanding of the biological process being observed. The lack of processing power is a bottle neck in acquiring results. Comparative genomics is a good example since it includes all the ingredients: huge and ever growing datasets, complex applications that demands large computational resources and new mathematical and statistical models for analysing and synthetizing genomic information. A promising approach to address such massive data sets is the creation of new computer software that makes effective use of parallel processing.
This proposal pursues the linking of different research domains to come up with a coordinated multi-disciplinary approach in the development of tools targeting Big-Data and computationally intensive scientific applications. Generic solutions for Big-Data storage, management, distribution, processing and final analysis will be developed. These solutions will target a broad range of scientific applications, in concrete, as proof-of-concept they will be implemented in the ‘Comparative Genomics’ field of bioinformatics and biomedical domains. Applications such as the detection of main evolutionary events, new comparative genomics’ models that can be evaluated experimentally, for inter-species evolutionary distance, the composition of the k-mers dictionaries for each specie, or customising symbolic computing methods to determine the consensus tree from a sequence of trees with application in multiple sequence alignments, phylogenetic studies, clustering algorithms, etc. present in diverse fields of bioinformatics, from NGS-DNA assembly to gene-expression, all of them well suited applications to apply HPC-CC approaches and with high and attractive potential for commercialization.

Coordinator

UNIVERSIDAD DE MALAGA

Address

Avda Cervantes, Num. 2
29016 Malaga

Spain

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 403 440,91

Administrative Contact

María Jesús Morales Caparrós (Prof.)

Participants (5)

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RISC SOFTWARE GMBH

Austria

EU Contribution

€ 752 191,11

UNIVERSITAT LINZ

Austria

EU Contribution

€ 233 233,44

INTEGROMICS SL ITG

Spain

EU Contribution

€ 368 305,57

SERVICIO ANDALUZ DE SALUD

Spain

EU Contribution

€ 233 418,24

BAYERISCHE AKADEMIE DER WISSENSCHAFTEN

Germany

EU Contribution

€ 625 743,36

Project information

Grant agreement ID: 324554

Status

Closed project

  • Start date

    1 February 2013

  • End date

    31 January 2017

Funded under:

FP7-PEOPLE

  • Overall budget:

    € 2 616 332,63

  • EU contribution

    € 2 616 332,63

Coordinated by:

UNIVERSIDAD DE MALAGA

Spain