A genetic stochastic process model for genome-wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data-Reference-Cited by-同舟云学术

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A genetic stochastic process model for genome-wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data

Published:2017-06-21 Issue:7 Volume:41 Page:620-635
ISSN:0741-0395
Container-title:Genetic Epidemiology
language:en
Short-container-title:Genet. Epidemiol.

Author:

He Liang¹^ORCID,Zhbannikov Ilya¹,Arbeev Konstantin G.¹,Yashin Anatoliy I.¹,Kulminski Alexander M.¹

Affiliation:

1. Biodemography of Aging Research Unit; Social Science Research Institute, Duke University; Durham NC USA

Funder

National Institute on Aging

National Heart, Lung, and Blood Institute

National Human Genome Research Institute

Publisher

Wiley

Subject

Genetics (clinical),Epidemiology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/gepi.22058/fullpdf

Reference74 articles.

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2. Information Theory and an Extension of the Maximum Likelihood Principle

3. Genetic model for longitudinal studies of aging, health, and longevity and its potential application to incomplete data;Arbeev;Journal of Theoretical Biology,2009

4. Joint analyses of longitudinal and time-to-event data in research on aging: Implications for predicting health and survival;Arbeev;Frontiers in Public Health,2014

5. Ascher , U. M. Petzold , L. R. 1998 Computer methods for ordinary differential equations and differential-algebraic equations

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