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PhenoMeNal

PhenoMeNal: A comprehensive and standardised e-infrastructure for analysing medical metabolic phenotype data

Total Cost €

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EC-Contrib. €

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Partnership

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 PhenoMeNal project word cloud

Explore the words cloud of the PhenoMeNal project. It provides you a very rough idea of what is the project "PhenoMeNal" about.

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Project "PhenoMeNal" data sheet

The following table provides information about the project.

Coordinator
EUROPEAN MOLECULAR BIOLOGY LABORATORY 

Organization address
address: Meyerhofstrasse 1
city: HEIDELBERG
postcode: 69117
website: http://www.embl.de

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Project website http://phenomenal-h2020.eu/home/
 Total cost 8˙005˙909 €
 EC max contribution 7˙684˙919 € (96%)
 Programme 1. H2020-EU.1.4.1.3. (Development, deployment and operation of ICT-based e-infrastructures)
 Code Call H2020-EINFRA-2014-2
 Funding Scheme RIA
 Starting year 2015
 Duration (year-month-day) from 2015-09-01   to  2018-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    EUROPEAN MOLECULAR BIOLOGY LABORATORY DE (HEIDELBERG) coordinator 1˙848˙460.00
2    IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE UK (LONDON) participant 1˙232˙095.00
3    UPPSALA UNIVERSITET SE (UPPSALA) participant 916˙655.00
4    THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD UK (OXFORD) participant 777˙761.00
5    LEIBNIZ-INSTITUT FUR PFLANZENBIOCHEMIE DE (Halle) participant 632˙500.00
6    UNIVERSITEIT LEIDEN NL (LEIDEN) participant 528˙930.00
7    COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES FR (PARIS 15) participant 379˙749.00
8    UNIVERSITAT DE BARCELONA ES (BARCELONA) participant 365˙937.00
9    THE UNIVERSITY OF BIRMINGHAM UK (BIRMINGHAM) participant 280˙376.00
10    INSTITUT NATIONAL DE RECHERCHE POUR L'AGRICULTURE, L'ALIMENTATION ET L'ENVIRONNEMENT FR (PARIS CEDEX 07) participant 276˙833.00
11    CONSORZIO INTERUNIVERSITARIO RISONANZE MAGNETICHE DI METALLO PROTEINE IT (FIRENZE) participant 225˙750.00
12    CENTRO DI RICERCA, SVILUPPO E STUDI SUPERIORI IN SARDEGNA SOCIETÀ A RESPONSABILITÀ LIMITATA IT (PULA CAGLIARI) participant 203˙995.00
13    BIOBANKS AND BIOMOLECULAR RESOURCESRESEARCH INFRASTRUCTURE CONSORTIUM(BBMRI-ERIC) AT (GRAZ) participant 15˙875.00
14    SIB INSTITUT SUISSE DE BIOINFORMATIQUE CH (GENEVE) participant 0.00

Map

 Project objective

In the coming decade a significant number of the 500.000.000 European (EU/EEA) citizens will have their genome determined routinely. This will be complemented with much cheaper (currently ~20 Euro per measurement) acquisition of the metabolome of biofluids (e.g. urine, saliva, blood plasma) which will link the genotype with metabolome data that captures the highly dynamic phenome and exposome of patients. Having such low cost solutions will enable, for the first time, the development of a truly personalised and evidence-based medicine founded on hard scientific measurements. The exposome includes the metabolic information resulting from all the external influences on the human organism such as age, behavioural factors like exercise and nutrition or other environmental factors. Considering that the amount of data generated by molecular phenotyping exceeds the data volume of personal genomes by at least an order of magnitude, the collection of such information will pose dramatic demands on biomedical data management and compute capabilities in Europe. For example, a single typical National Phenome Centre, managing only around 100,000 human samples per year, can generate more than 2 Petabytes of data during this period alone. A scale-up to sizable portions of the European population over time will require data analysis services capable to work on exabyte-scale amounts of biomedical phenotyping data, for which no viable solution exists at the moment. The PhenoMeNal project will develop and deploy an integrated, secure, permanent, on-demand service-driven, privacy-compliant and sustainable e-infrastructure for the processing, analysis and information-mining of the massive amount of medical molecular phenotyping and genotyping data that will be generated by metabolomics applications now entering research and clinic.

 Deliverables

List of deliverables.
D9.4 Updated report on existing software tools, workflows and analytical pipelines supported in PhenoMeNal Documents, reports 2019-10-07 09:07:40
D3.4.1 Two training workshops on omics data deposition, grid processing, dissemination and access Other 2019-10-07 09:07:40
D9.5.4 Updated Compute Virtual Machine Image 4 Other 2019-10-07 09:07:40
D9.5.2 Updated Data Processing Virtual Machine Image 2 Other 2019-10-07 09:07:40
D9.2.5 Portal Virtual Machine Image 5 that is capable of integrating other PhenoMeNal-VMIs (in local federated clouds) and make all functionality available via command-line, Web-APIs, and graphical user interfaces Other 2019-10-07 09:07:40
D4.3 Consensus agreement document from the working groups Documents, reports 2019-10-07 09:07:40
D9.5.3 Updated Services Virtual Machine Image 3 Other 2019-10-07 09:07:40
D6.5 Training and online tutorial for the general use of the PhenoMeNal Websites, patent fillings, videos etc. 2019-10-07 09:07:40
D4.4 Report on State-of-The-Art and Perspectives in the field Documents, reports 2019-10-07 09:07:40
D9.5.1 Updated Preprocess Virtual Machine Image 1 Other 2019-10-07 09:07:40
D8.4.2 Reference implementation guidelines and validation rules Other 2019-10-07 09:07:40
D6.4 Participating Biobanks and repositories connected to the VRC Other 2019-10-07 09:07:40
D5.4 A federated cloud/grid system running on partners’ infrastructures for public data and tools. All services available. Operational installation at ICL clinical site for decision support Other 2019-10-07 09:07:40
D5.3 Operational grid/cloud allowing for combining data, tools, and compute VMIs. Most services available. Functional integration with EGI federated cloud/grid for compute resources. Demonstrated analysis on private/sensitive data in secure environment Other 2019-10-07 09:07:40
D9.3 Report API access to PhenoMeNal Resources Documents, reports 2019-10-07 09:07:40
D3.4.2 Two training workshops on omics data deposition, grid processing, dissemination and access Other 2019-10-07 09:07:40
D1.5.3 Updated Data Management Plan (H2020 Open Research Data Pilot) Open Research Data Pilot 2019-10-07 09:07:40
D9.5.5 Updated Portal Virtual Machine Image 5 Other 2019-10-07 09:07:40
D7.1.2 Workshop 2 on best practices in handling sensitive human data, taking into account National and Institutional legal policies Other 2019-10-07 09:07:40
\"D3.3.2 Web-based Tutorial release 2 about \"\"Metabolomics Data Deposition and Analysis through PhenoMeNal”, in the form of video clips\" Websites, patent fillings, videos etc. 2019-10-07 09:07:40
D8.4.1 Specifications for derived data matrices specifications and terminology for description of analysis and statistical results Other 2019-10-07 09:07:40
D8.2 Modularized ISA model and format: biospecimen centric schema, corresponding xml schemas, reference implementation guidelines and validation rules Other 2019-10-07 09:07:40
D9.2.1 PhenoMeNal-Preprocess Virtual Machine Image 1 to enable data producers to locally process raw data into standard formats supported in PhenoMeNal Other 2019-10-07 09:07:39
D7.1.1 Workshop 1 on best practices in handling sensitive human data, taking into account National and Institutional legal policies Other 2019-10-07 09:07:38
D8.3 nmrML, mzML data exchange formats and associated terminologies for instrument raw, with reference implementation guidelines and validation rules Other 2019-10-07 09:07:39
D7.2 Report on policies and procedures for sensitive human data management Documents, reports 2019-10-07 09:07:39
D5.2 A beta-version of PhenoMeNal integration VMI capable of proof- of-concept integration with other VMIs. Initial services online supporting PhenoMeNal data standards Other 2019-10-07 09:07:38
D9.2.4 Compute Virtual Machine Image 4 to enable standardised compute capabilities for all the grid supplying partners Other 2019-10-07 09:07:39
D9.2.3 Services Virtual Machine Image 3 to facilitate the PhenoMeNal toolsets and pipelines, both locally and in the grid Other 2019-10-07 09:07:39
D9.2.2 PhenoMeNal-Data Virtual Machine Image 2 to enable sharing and dissemination of standardised and processed omics data to participating online repositories, like MetaboLights Other 2019-10-07 09:07:39
D8.4 Signal processing and analysis data exchange format Other 2019-10-07 09:07:39
D7.4 Process to extract maximum information from sensitive datasets with minimum compromise, in collaboration with BBMRI and BioMedBridges Other 2019-10-07 09:07:39
D5.1 Build System with continuous integration, providing development snapshots of PhenoMeNal Virtual Machine Images Other 2019-10-07 09:07:38
D1.5.2 Updated Data Management Plan (H2020 Open Research Data Pilot) Open Research Data Pilot 2019-10-07 09:07:38
D4.2 Report describing the activity and output of working groups Documents, reports 2019-10-07 09:07:38
D4.1Report on requirements for relevant research centers producing and/or consuming metabolomics data with respect to computational aspects, data storage, and infrastructural needs Documents, reports 2019-10-07 09:07:38
\"D3.3.1 Web-based Tutorial release 1 about \"\"Metabolomics Data Deposition and Analysis through PhenoMeNal”, in the form of video clips\" Websites, patent fillings, videos etc. 2019-10-07 09:07:38
D8.1 Report on community standards for reporting, access and integrity supported in the PhenoMeNal grid; to be disseminated in a dedicated BioSharing page and via the project website Documents, reports 2019-10-07 09:07:39
D9.1 Report on existing software tools, workflows and analytical pipelines initially supported in the PhenoMeNal grid Documents, reports 2019-10-07 09:07:39
D6.3 Online user feedback form Websites, patent fillings, videos etc. 2019-10-07 09:07:38
D6.2 PhenoMeNal VRC (static) portal publicly available Websites, patent fillings, videos etc. 2019-10-07 09:07:38
D1.5.1 Data Management Plan (H2020 Open Research Data Pilot) Open Research Data Pilot 2019-10-07 09:07:38

Take a look to the deliverables list in detail:  detailed list of PhenoMeNal deliverables.

 Publications

year authors and title journal last update
List of publications.
2017 Stephanie Herman, Payam Emami Khoonsari, Obaid Aftab, Shibu Krishnan, Emil Strömbom, Rolf Larsson, Ulf Hammerling, Ola Spjuth, Kim Kultima, Mats Gustafsson
Mass spectrometry based metabolomics for in vitro systems pharmacology: pitfalls, challenges, and computational solutions
published pages: , ISSN: 1573-3882, DOI: 10.1007/s11306-017-1213-z
Metabolomics 13/7 2019-10-07
2017 Panteleimon G. Takis, Hartmut Schäfer, Manfred Spraul, Claudio Luchinat
Deconvoluting interrelationships between concentrations and chemical shifts in urine provides a powerful analysis tool
published pages: , ISSN: 2041-1723, DOI: 10.1038/s41467-017-01587-0
Nature Communications 8/1 2019-10-07
2018 Maria Caracausi, Veronica Ghini, Chiara Locatelli, Martina Mericio, Allison Piovesan, Francesca Antonaros, Maria Chiara Pelleri, Lorenza Vitale, Rosa Anna Vacca, Federica Bedetti, Maria Chiara Mimmi, Claudio Luchinat, Paola Turano, Pierluigi Strippoli, Guido Cocchi
Plasma and urinary metabolomic profiles of Down syndrome correlate with alteration of mitochondrial metabolism
published pages: , ISSN: 2045-2322, DOI: 10.1038/s41598-018-20834-y
Scientific Reports 8/1 2019-10-07
2017 Van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B.; Ebbels, Timothy M. D.; Giacomoni, Franck; Gonzalez-beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-garcia, Jose L.; Jimenez, Rafael C.; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I.; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moreno, Pablo; Moschonas, Nicholas K.; Neumann, Steffen; O’Donovan, Claire; Reczko, Martin; Rocca-serra, Philippe; Rosato, Antonio; Salek, Reza M.; Sansone, Susanna-assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A.; Spjuth, Ola; Thévenot, Etienne A.; Viant, Mark R.; Weber, Ralf J. M.; Willighagen, Egon L.; Zanetti, Gianluigi; Steinbeck, Christoph
The future of metabolomics in ELIXIR
published pages: , ISSN: 2046-1402, DOI: 10.17863/CAM.17780
F1000Research, 6 8 2019-10-07
2017 Linda S. L. Tan, Ajay Jasra, Maria De Iorio, Timothy M. D. Ebbels
Bayesian inference for multiple Gaussian graphical models with application to metabolic association networks
published pages: 2222-2251, ISSN: 1932-6157, DOI: 10.1214/17-AOAS1076
The Annals of Applied Statistics 11/4 2019-10-07
2018 Lifeng Ye, Maria De Iorio, Timothy M. D. Ebbels
Bayesian estimation of the number of protonation sites for urinary metabolites from NMR spectroscopic data
published pages: , ISSN: 1573-3882, DOI: 10.1007/s11306-018-1351-y
Metabolomics 14/5 2019-10-07
2017 Spicer, Rachel; Salek, RM; Moreno, P; Cañueto, C; Steinbeck, C
Navigating freely-available software tools for metabolomics analysis
published pages: , ISSN: 1573-3882, DOI: 10.17863/CAM.13427
Metabolomics 5 2019-10-07
2017 Rico Rueedi, Roger Mallol, Johannes Raffler, David Lamparter, Nele Friedrich, Peter Vollenweider, Gérard Waeber, Gabi Kastenmüller, Zoltán Kutalik, Sven Bergmann
Metabomatching: Using genetic association to identify metabolites in proton NMR spectroscopy
published pages: e1005839, ISSN: 1553-7358, DOI: 10.1371/journal.pcbi.1005839
PLOS Computational Biology 13/12 2019-10-07
2017 Maxime Chazalviel, Clément Frainay, Nathalie Poupin, Florence Vinson, Benjamin Merlet, Yoann Gloaguen, Ludovic Cottret, Fabien Jourdan
MetExploreViz: web component for interactive metabolic network visualization
published pages: 312-313, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/btx588
Bioinformatics 34/2 2019-10-07
2018 Mark D. Wilkinson, Susanna-Assunta Sansone, Erik Schultes, Peter Doorn, Luiz Olavo Bonino da Silva Santos, Michel Dumontier
A design framework and exemplar metrics for FAIRness
published pages: 180118, ISSN: 2052-4463, DOI: 10.1038/sdata.2018.118
Scientific Data 5 2019-10-07
2018 Antonio Rosato, Leonardo Tenori, Marta Cascante, Pedro Ramon De Atauri Carulla, Vitor A. P. Martins dos Santos, Edoardo Saccenti
From correlation to causation: analysis of metabolomics data using systems biology approaches
published pages: , ISSN: 1573-3882, DOI: 10.1007/s11306-018-1335-y
Metabolomics 14/4 2019-10-07
2017 Kenneth Haug, Reza M Salek, Christoph Steinbeck
Global open data management in metabolomics
published pages: 58-63, ISSN: 1367-5931, DOI: 10.1016/j.cbpa.2016.12.024
Current Opinion in Chemical Biology 36 2019-10-07
2017 Vitaly A. Selivanov, Adrián Benito, Anibal Miranda, Esther Aguilar, Ibrahim Halil Polat, Josep J. Centelles, Anusha Jayaraman, Paul W. N. Lee, Silvia Marin, Marta Cascante
MIDcor, an R-program for deciphering mass interferences in mass spectra of metabolites enriched in stable isotopes
published pages: , ISSN: 1471-2105, DOI: 10.1186/s12859-017-1513-3
BMC Bioinformatics 18/1 2019-10-07
2016 Anita Bandrowski, Ryan Brinkman, Mathias Brochhausen, Matthew H. Brush, Bill Bug, Marcus C. Chibucos, Kevin Clancy, Mélanie Courtot, Dirk Derom, Michel Dumontier, Liju Fan, Jennifer Fostel, Gilberto Fragoso, Frank Gibson, Alejandra Gonzalez-Beltran, Melissa A. Haendel, Yongqun He, Mervi Heiskanen, Tina Hernandez-Boussard, Mark Jensen, Yu Lin, Allyson L. Lister, Phillip Lord, James Malone, Elisabetta Manduchi, Monnie McGee, Norman Morrison, James A. Overton, Helen Parkinson, Bjoern Peters, Philippe Rocca-Serra, Alan Ruttenberg, Susanna-Assunta Sansone, Richard H. Scheuermann, Daniel Schober, Barry Smith, Larisa N. Soldatova, Christian J. Stoeckert, Chris F. Taylor, Carlo Torniai, Jessica A. Turner, Randi Vita, Patricia L. Whetzel, Jie Zheng
The Ontology for Biomedical Investigations
published pages: e0154556, ISSN: 1932-6203, DOI: 10.1371/journal.pone.0154556
PLOS ONE 11/4 2019-10-07
2016 Nils ePaulhe; Benjamin eMerlet; Yoann eGloaguen; Clément eFrainay; Nathalie ePoupin; Fabien eJourdan; Maxime eChazalviel; Florence eVinson; Franck eGiacomoni
A computational solution to automatically map metabolite libraries in the context of genome scale metabolic networks
published pages: , ISSN: 2296-889X, DOI: 10.3389/fmolb.2016.00002
Frontiers in Molecular Biosciences, Vol 3 (2016) 3 2019-10-07
2017 Panteleimon G. Takis, Leonardo Tenori, Enrico Ravera, Claudio Luchinat
Gelified Biofluids for High-Resolution Magic Angle Spinning 1 H NMR Analysis: The Case of Urine
published pages: 1054-1058, ISSN: 0003-2700, DOI: 10.1021/acs.analchem.6b04318
Analytical Chemistry 89/2 2019-10-07
2016 Ibrahim Karaman, Diana L. S. Ferreira, Claire L. Boulangé, Manuja R. Kaluarachchi, David Herrington, Anthony C. Dona, Raphaële Castagné, Alireza Moayyeri, Benjamin Lehne, Marie Loh, Paul S. de Vries, Abbas Dehghan, Oscar H. Franco, Albert Hofman, Evangelos Evangelou, Ioanna Tzoulaki, Paul Elliott, John C. Lindon, Timothy M. D. Ebbels
Workflow for Integrated Processing of Multicohort Untargeted 1 H NMR Metabolomics Data in Large-Scale Metabolic Epidemiology
published pages: 4188-4194, ISSN: 1535-3893, DOI: 10.1021/acs.jproteome.6b00125
Journal of Proteome Research 15/12 2019-10-07
2016 Stefano Cacciatore, Leonardo Tenori, Claudio Luchinat, Phillip R. Bennett, David A. MacIntyre
KODAMA: an R package for knowledge discovery and data mining
published pages: btw705, ISSN: 1367-4803, DOI: 10.1093/bioinformatics/btw705
Bioinformatics 2019-10-07
2016 Edoardo Saccenti, Giulia Menichetti, Veronica Ghini, Daniel Remondini, Leonardo Tenori, Claudio Luchinat
Entropy-Based Network Representation of the Individual Metabolic Phenotype
published pages: 3298-3307, ISSN: 1535-3893, DOI: 10.1021/acs.jproteome.6b00454
Journal of Proteome Research 15/9 2019-10-07
2016 Benjamin J. Blaise, Gonçalo Correia, Adrienne Tin, J. Hunter Young, Anne-Claire Vergnaud, Matthew Lewis, Jake T. M. Pearce, Paul Elliott, Jeremy K. Nicholson, Elaine Holmes, Timothy M. D. Ebbels
Power Analysis and Sample Size Determination in Metabolic Phenotyping
published pages: 5179-5188, ISSN: 0003-2700, DOI: 10.1021/acs.analchem.6b00188
Analytical Chemistry 88/10 2019-10-07
2016 Philippe Rocca-Serra, Reza M. Salek, Masanori Arita, Elon Correa, Saravanan Dayalan, Alejandra Gonzalez-Beltran, Tim Ebbels, Royston Goodacre, Janna Hastings, Kenneth Haug, Albert Koulman, Macha Nikolski, Matej Oresic, Susanna-Assunta Sansone, Daniel Schober, James Smith, Christoph Steinbeck, Mark R. Viant, Steffen Neumann
Data standards can boost metabolomics research, and if there is a will, there is a way
published pages: , ISSN: 1573-3882, DOI: 10.1007/s11306-015-0879-3
Metabolomics 12/1 2019-10-07

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