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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.

Field of science

  • /natural sciences/mathematics/applied mathematics/mathematical model
  • /natural sciences/mathematics/applied mathematics/statistics and probability
  • /natural sciences/computer and information sciences/software

Call for proposal

FP7-PEOPLE-2012-IAPP
See other projects for this call

Funding Scheme

MC-IAPP - Industry-Academia Partnerships and Pathways (IAPP)

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)

RISC SOFTWARE GMBH
Austria
EU contribution
€ 752 191,11
Address
Softwarepark 35
4232 Hagenberg
Activity type
Research Organisations
Administrative Contact
Michael Thomas Krieger (Mr.)
UNIVERSITAT LINZ
Austria
EU contribution
€ 233 233,44
Address
Altenberger Strasse 69
4040 Linz
Activity type
Higher or Secondary Education Establishments
Administrative Contact
Sepp Hochreiter (Prof.)
INTEGROMICS SL ITG
Spain
EU contribution
€ 368 305,57
Address
Avenida De Innovacion Granada Parque Tecnologia Ciencas De La Salud 1 Bic
18100 Armilla -Granada
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Administrative Contact
Judit Fernandez Rodríguez (Mrs.)
SERVICIO ANDALUZ DE SALUD
Spain
EU contribution
€ 233 418,24
Address
Avenida De La Constitucion 18
41071 Sevilla
Activity type
Public bodies (excluding Research Organisations and Secondary or Higher Education Establishments)
Administrative Contact
Elena Martin-Bautista (Dr.)
BAYERISCHE AKADEMIE DER WISSENSCHAFTEN
Germany
EU contribution
€ 625 743,36
Address
Alfons-goppel-strasse 11
80539 Muenchen
Activity type
Research Organisations
Administrative Contact
Victor Apostolescu (Dr.)