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This work has been designed in support of the research article entitled "Enhancing metabolomics research through data mining", which proposed a methodological data handling guideline.
This work has been designed to supply methodological data mining guidelines, describing systematically the steps to be followed in metabolomics data exploration.
A summary of the methodological data and study results can be found in Tables 5, 6 and 7. Seven of the studies were retrospective studies and one was prospective.
Demographic and methodological data were also extracted for the following confounding factors: age, sex, sports discipline, competition level, seasonal phase, and methods for assessing body composition, energy intake, and/or TEE.
In particular, the presence of methodological data biases and the topological similarity between networks with small microscopic overlap can be detected clearly and at low computational cost.
Methodological data included the country setting, year of analysis, modeling approach, time horizon, population, outcomes reported, and data sources used.
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RC was involved in methodological development, data collection, data input and analysis.
JM-G was involved in methodological development, data collection, data input and statistical analysis.
DA was involved in methodological development, data collection, data input and analysis and presentation at regional conference.
KK, TB, SB, MF and KN were involved in methodological development, data collection, data input and analysis.
LB, AB, M-JF, NG, and MJ were involved in methodological development, data collection and data input.
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