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Discovering functional protein-RNA interactions through data integration and machine learning.

Objective

RNA-binding proteins are implicated across a wide spectrum of human genetic disorders, with molecular mechanisms ranging from aggregation of proteins and RNAs to defects in splicing and translation. Examples include heterogeneous and life-threatening genetic disorders such as Diamond-Blackfan anaemia, spinocerebellar ataxia and amyotrophic lateral sclerosis (ALS) among others.

The DeepRNA project targets genetic diseases via disease-associated variants in the human transcriptome and is enabled by recent data on expression quantitative trait loci (eQTLs) and experimentally determined RNA-protein and RNA-RNA interactions. The data will be complemented with high-quality RNA-protein interaction predictions carried out in the host group that has a strong track record in computing and validating RNA-protein associations.

To my knowledge the use of eQTL variants to study RNA-protein interactions is a novel approach and is useful for developing new tools for personalised medicine. My approach will expand the human interactome in a genome-wide manner beyond experimental data, which is currently available for only 352 of the 1,542 recently described RNA-binding proteins. Complementing experimentally determined interactions with predictions will allow me to expand my analyses of the human interactome to the genomic scale while maintaining accuracy, by using the experimental dataset as a gold standard. I will employ methods such as graph partitioning and graph neural network encoding to rationalise the effects of disease-associated variants on the human interaction network, and make quantitative predictions of polymorphisms associated with genetic diseases, thereby aiding personalised medicine.

I am confident that this fellowship will equip me with the domain knowledge, independence and transferrable skills to confidently and creatively build an interdisciplinary, globally recognised research team within Europe that will focus on medically relevant human signalling systems.

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MSCA-IF-EF-ST - Standard EF

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-IF-2017

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Coordinator

FUNDACIO CENTRE DE REGULACIO GENOMICA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 158 121,60
Address
CARRER DOCTOR AIGUADER 88
08003 Barcelona
Spain

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Region
Este Cataluña Barcelona
Activity type
Research Organisations
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 158 121,60
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