Massive increases in analytical throughput together with reductions in costs have enabled multi-omics studies to be routinely performed at a scale not previously imagined. Two main barriers hamper our ability to reveal the mechanism behind a specific genotype-phenotype link: the cross-talk between multiple molecular layers cannot be properly assessed by a reductionist approach that analyses each omics layer in isolation; and the ever-growing amount of buried information in scientific literature and public omics datasets cannot be extracted without intelligent computational approaches.
GLOMICAVE project allows streamlining the experimental design, the analysis and integration of large-scale omics experiments by maximizing the utility of pre-existing massive omics datasets and scientific literature. The aim is to identify and understand new links between (non-humans) genotype and phenotype. The main outcome will be a multi-omics data analysis cloud-based platform, relying on Big Data Analytics and Artificial Intelligence.
GLOMICAVE integrative approach will be validated in 3 different industrial sectors (i.e., livestock, agro-biotechnology and environment) addressing specific challenges in 6 business cases, which will pave the way for further uptake in other business areas.
TREE will be the developer of the cloud-based Big Data platform for the collection, storage, processing and exploitation of data from the different -omic sources, coming from both end users and public repositories. Although the data ingestion, preparation and analysis modules will be created by different partners in four work packages, the one led by TREE aims at integrating them.
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 952908.
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