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Genomic Data-Fusion Platform for Omics-Driven Precision Medicine

Project description

A novel platform for omics data analysis

Omics technologies have revolutionised the way we study the genome, epigenome, metabolome and proteome, providing a vast amount of information related to clinical profiling and disease characterisation. However, we lack the comprehensive analytics tools that would assist the biopharmaceutical sector to exploit omics data for biomedical innovations and precision medicine. Towards this goal, the EU-funded GENETTA project is working on a platform capable of analysing large amounts of heterogeneous multi-scale omics data. The implementation of this platform into existing data science resources of biopharmaceutical companies is expected to optimise and guide their discovery process.

Objective

This PoC project aims to pave the road to commercialize a comprehensive data analytics platform enabling data-driven biomedical innovation and precision medicine. The platform is specifically designed to efficiently fuse and mine heterogeneous omic data, including genomes,
epigenomes, proteomes, metabolomes, patient clinical profiles, drugs and their chemical similarities, disease and other
ontologies, and other relevant omic data. The goal of this development is to provide the most advanced software platform for
fusion and analytics of numerous heterogeneous multi-scale omic data that takes advantage of novel non-negative matrix trifactorization
(NMTF)-based and network mining algorithms, providing dramatic improvements in the number and type of
fused data, quantity of data, computational efficiency and biomedical accuracy compared to the most advanced omic data
analytics platforms currently existing.

The main goal of the PoC is to close the gap between the research results of ERC Consolidator Grant, ICON-BIO, and the production of a
commercial data analytics platform for the bio-pharmaceutical sector. In particular, the solution will target biopharma
companies to embed the platform into their existing Data Science resources and enable effective and
efficient application of the platform’s explainable AI methods (resulting from ICON-BIO) to optimize and guide their discovery
processes. The result of this effort will be the achievement of a market-ready Data Analytics Platform.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

ERC-POC - Proof of Concept Grant

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Call for proposal

(opens in new window) ERC-2020-PoC

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Host institution

BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACION
Net EU contribution
€ 150 000,00
Address
CALLE JORDI GIRONA 31
08034 BARCELONA
Spain
Region
Este Cataluña Barcelona
Activity type
Research Organisations
Links
Total cost
No data

Beneficiaries (1)