Project description
Training researchers in large data analysis
European researchers have significantly contributed to the large genomic, transcriptomic and clinical data sets assembled from patients with chronic diseases. Advances in information science provide opportunities for increased use of these data sets. However, few researchers have the needed informatics skills and knowledge of the latest data protection principles. The EU-funded HELICAL project will develop an interdisciplinary training programme for 15 PhD students. It will use autoimmune vasculitis as a paradigm to provide training in data analysis. The 36-month training programme will focus on the application of informatics to such data sets to gain new biological insights as well as the translation of biological into practical clinical outputs. It also aims to develop strategies to manage the ethical constraints imposed on such studies.
Objective
European researchers have made leading contributions to the large genomic, transcriptomic and clinical datasets from patients with chronic diseases. Advances in information science provide unprecedented opportunities for using these datasets to elucidate the complex biology of these disorders, its influence by environmental triggers, and to personalise their management. Currently, exploitation of these opportunities is limited by a shortage of researchers with the required informatics skills and knowledge of requisite data protection principles. HELICAL addresses this unmet need by developing a trans-sectoral and interdisciplinary training programme that builds on the expertise and existing collaborations of its partners. It provides 15 early stage researchers with training in analysis of large datasets, using autoimmune vasculitis as a paradigm as it is scalable, and as comprehensive biological and clinical datasets are already available. The HELICAL training program focuses on three complementary areas: application of informatics to such datasets to gain new biological insights; translation of these into practical clinical outputs and management of ethical constraints imposed on such studies. The programme will be delivered through a multidisciplinary, trans-sectoral partnership of Academic and Industry researchers with expertise in basic biomedical research, epidemiology, statistics, machine learning, health data governance and ethics. Therefore, HELICAL exploits recent advances in data science to link research datasets with longitudinal healthcare records, based on the robust ethical foundation required for linkage studies using near-patient data, to address key experimental questions. The results will have obvious potential for transforming healthcare in the field of autoimmune disease. The training provided addresses a key skills gap in the European workforce and should make the ESR eminently employable in academic, industrial and clinical sectors.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciences computer and information sciences data science
- natural sciences computer and information sciences computer security data protection
- medical and health sciences health sciences public health epidemiology
- medical and health sciences basic medicine immunology autoimmune diseases
- natural sciences computer and information sciences artificial intelligence machine learning
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.1. - Fostering new skills by means of excellent initial training of researchers
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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.
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.
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-ITN - Marie Skłodowska-Curie Innovative Training Networks (ITN)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-ITN-2018
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D02 CX56 Dublin
Ireland
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Participants (14)
Participation ended
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75006 PARIS
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08036 Barcelona
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28006 MADRID
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LS2 9JT Leeds
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08036 BARCELONA
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1090 WIEN
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100 44 STOCKHOLM
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08007 Barcelona
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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.
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1020 Wien
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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.
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68330 Huningue
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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.
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9860 OOSTERZELE
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G12 8QQ Glasgow
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8803 RUESCHLIKON
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9007 St. Gallen
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Partners (10)
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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NE1 7RU Newcastle Upon Tyne
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751 05 Uppsala
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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9000 GENT
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116 36 Praha 1
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08193 Cerdanyola Del Valles
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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39011 Santander
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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.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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.
CB10 1DR Cambridge
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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.
08007 BARCELONA
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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.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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.
75015 Paris
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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.
D08P X8H Dublin
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.