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

被引:4
|
作者
Giampieri, Enrico [2 ,5 ]
Remondini, Daniel [2 ,5 ]
Bacalini, Maria Giulia [1 ,2 ]
Garagnani, Paolo [1 ,2 ]
Pirazzini, Chiara [1 ,2 ]
Yani, Stella Lukas [1 ,2 ,3 ]
Giuliani, Cristina [1 ,2 ]
Menichetti, Giulia [2 ,5 ]
Zironi, Isabella [2 ,5 ]
Sala, Claudia [2 ,5 ]
Capri, Miriam [1 ,2 ]
Franceschi, Claudio [1 ,2 ]
Buerkle, Alexander [4 ]
Castellani, Gastone [2 ,5 ]
机构
[1] Univ Bologna, Dept Expt Diagnost & Specialty Med, Bologna, Italy
[2] Univ Bologna, Interdepartmental Ctr Galvani CIG, Bologna, Italy
[3] Univ Innsbruck, Inst Biomed Aging Res, A-6020 Innsbruck, Austria
[4] Univ Konstanz, Dept Biol, Mol Toxicol Grp, D-78457 Constance, Germany
[5] Univ Bologna, Dept Phys & Astron, Bologna, Italy
关键词
Biomarkers; Biological age; Chronological age; Statistics models; MARK-AGE; LOG-NORMAL DISTRIBUTION; MISSING-DATA; METHYLATION; MECHANISMS; EXPRESSION;
D O I
10.1016/j.mad.2015.07.001
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
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: (C) 2015 Published by Elsevier Ireland Ltd.
引用
收藏
页码:45 / 53
页数:9
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