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Open J. Stat., 2012, том 2, выпуск 1, страницы 73–87
(Mi ojs1)
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Statistical methods of SNP data analysis and applications
A. Bulinskia, O. Butkovskya, V. Sadovnichya, A. Shashkina, P. Yaskova, A. Balatskiyb, L. Samokhodskayab, V. Tkachukb a Faculty of Mathematics and Mechanics, Moscow State University, Moscow, Russia
b Faculty of Basic Medicine, Moscow State University, Moscow, Russia
Аннотация:
We develop various statistical methods important for multidimensional genetic data analysis. Theorems justifying application of these methods are established. We concentrate on the multifactor dimensionality reduction, logic regression, random forests, stochastic gradient boosting along with their new modifications. We use complementary approaches to study the risk of complex diseases such as cardiovascular ones. The roles of certain combinations of single nucleotide polymorphisms and non-genetic risk factors are examined. To perform the data analysis concerning the coronary heart disease and myocardial infarction the Lomonosov Moscow State University supercomputer “Chebyshev” was employed.
DOI:
https://doi.org/10.4236/ojs.2012.21008
Реферативные базы данных:
Тип публикации:
Статья Поступила в редакцию: 09.10.2011 Исправленный вариант: 16.11.2011 Принята в печать:20.11.2011
Язык публикации: английский
Образцы ссылок на эту страницу:
http://mi.mathnet.ru/ojs1
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