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Statistical strategies and stochastic predictive models for the MARK-AGE data

Authors :
Enrico Giampieri
Daniel Remondini
Claudia Sala
Claudio Franceschi
Chiara Pirazzini
Cristina Giuliani
Miriam Capri
Maria Giulia Bacalini
Paolo Garagnani
Alexander Bürkle
Isabella Zironi
Giulia Menichetti
Stella Lukas Yani
Gastone Castellani
Giampieri, Enrico
Remondini, Daniel
Bacalini, Maria Giulia
Garagnani, Paolo
Pirazzini, Chiara
Yani, Stella Luka
Giuliani, Cristina
Menichetti, Giulia
Zironi, Isabella
Sala, Claudia
Capri, Miriam
Franceschi, Claudio
Bürkle, Alexander
Castellani, Gastone
Publication Year :
2015

Abstract

MARK-AGE aims at the identification of biomarkers of human aging capable of discriminating between the chronological age and the effective functional status of the organism. To achieve this, given the structure of the collected data, a proper statistical analysis has to be performed, as the structure of the data are non trivial and the number of features under study is near to the number of subjects used, requiring special care to avoid overfitting. Here we described some of the possible strategies suitable for this analysis. We also include a description of the main techniques used, to explain and justify the selected strategies. Among other possibilities, we suggest to model and analyze the data with a three step strategy

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....2250d752be79d16fa273f516b125fa33