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Advances in metabolome information retrieval: turning chemistry into biology. Part II: biological information recovery
Author(s) -
Tebani Abdellah,
Afonso Carlos,
Bekri Soumeya
Publication year - 2018
Publication title -
journal of inherited metabolic disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.462
H-Index - 102
eISSN - 1573-2665
pISSN - 0141-8955
DOI - 10.1007/s10545-017-0080-0
Subject(s) - metabolomics , metabolome , computer science , data science , preprocessor , computational biology , systems biology , bioinformatics , biology , artificial intelligence
This work reports the second part of a review intending to give the state of the art of major metabolic phenotyping strategies. It particularly deals with inherent advantages and limits regarding data analysis issues and biological information retrieval tools along with translational challenges. This Part starts with introducing the main data preprocessing strategies of the different metabolomics data. Then, it describes the main data analysis techniques including univariate and multivariate aspects. It also addresses the challenges related to metabolite annotation and characterization. Finally, functional analysis including pathway and network strategies are discussed. The last section of this review is devoted to practical considerations and current challenges and pathways to bring metabolomics into clinical environments.