PhenoMeNal: processing and analysis of metabolomics data in the cloud | Zendy

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PhenoMeNal: processing and analysis of metabolomics data in the cloud

Author(s) -

Kristian Peters,

James Bradbury,

Sven Bergmann,

Marco Capuccini,

Marta Cascante,

Pedro de Atauri,

Timothy M. D. Ebbels,

Carles Foguet,

Robert C. Glen,

Alejandra González-Beltrán,

Ulrich L. Günther,

Evangelos Handakas,

Thomas Hankemeier,

Kenneth Haug,

Stephanie Herman,

Petr Holub,

Massimiliano Izzo,

Daniel Jacob,

David Johnson,

Fabien Jourdan,

Namrata Kale,

İbrahim Karaman,

Bita Khalili,

Payam Emami Khoonsari,

Kim Kultima,

Samuel Lampa,

Anders Larsson,

Christian Ludwig,

Pablo Moreno,

Steffen Neumann,

Jon Ander Novella,

Claire O’Donovan,

Jake T. M. Pearce,

Alina Peluso,

Marco Enrico Piras,

Luca Pireddu,

Michelle A.C. Reed,

Philippe RoccaSerra,

Pierrick Roger,

Antonio Rosato,

Rico Rueedi,

Christoph Ruttkies,

Noureddin Sadawi,

Reza M. Salek,

SusannaAssunta Sansone,

Vitaly A. Selivanov,

Ola Spjuth,

Daniel Schober,

Etienne Thévenot,

Mattia Tomasoni,

Merlijn van Rijswijk,

Michael Van Vliet,

Mark R. Viant,

Ralf J. M. Weber,

Gianluigi Zanetti,

Christoph Steinbeck

Publication year - 2018

Publication title -

gigascience

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.947

H-Index - 54

ISSN - 2047-217X

DOI - 10.1093/gigascience/giy149

Subject(s) - cloud computing , workflow , computer science , interoperability , data science , world wide web , database , operating system

Metabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organism's metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological, and many other applied biological domains. Its computationally intensive nature has driven requirements for open data formats, data repositories, and data analysis tools. However, the rapid progress has resulted in a mosaic of independent, and sometimes incompatible, analysis methods that are difficult to connect into a useful and complete data analysis solution.

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