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Study of statistical parameters to perform a convenient prediction of different endocrine phenotypes in sportsmen based on metabonomic data
Author(s) -
Alain Paris,
Boris Labrador,
FrançoisXavier Lejeune,
Aziz Zoubai,
Cécile Canlet,
Jérôme Molina,
Michel Guinot,
Armand Mégret,
JeanChristophe Thalabard,
Michel Rieu
Publication year - 2011
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
Subject(s) - computer science , phenotype , endocrine system , data mining , artificial intelligence , machine learning , computational biology , biology , medicine , genetics , gene , hormone

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