Explore the words cloud of the PhenoMeNal project. It provides you a very rough idea of what is the project "PhenoMeNal" about.
The following table provides information about the project.
Coordinator |
EUROPEAN MOLECULAR BIOLOGY LABORATORY
Organization address contact info |
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 |
Take a look of project's partnership.
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.
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 PhenoMeNalâ€, 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 PhenoMeNalâ€, 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.
year | authors and title | journal | last update |
---|---|---|---|
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 |
Are you the coordinator (or a participant) of this project? Plaese send me more information about the "PHENOMENAL" project.
For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.
Send me an email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.
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The information about "PHENOMENAL" are provided by the European Opendata Portal: CORDIS opendata.