Evaluation of Penalized and Nonpenalized Methods for Disease Prediction with Large-Scale Genetic Data
المؤلفون المشاركون
Won, Sungho
Choi, Hosik
Park, Suyeon
Lee, Juyoung
Park, Changyi
Kwon, Sunghoon
المصدر
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-08-04
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
Owing to recent improvement of genotyping technology, large-scale genetic data can be utilized to identify disease susceptibility loci and this successful finding has substantially improved our understanding of complex diseases.
However, in spite of these successes, most of the genetic effects for many complex diseases were found to be very small, which have been a big hurdle to build disease prediction model.
Recently, many statistical methods based on penalized regressions have been proposed to tackle the so-called “large P and small N” problem.
Penalized regressions including least absolute selection and shrinkage operator (LASSO) and ridge regression limit the space of parameters, and this constraint enables the estimation of effects for very large number of SNPs.
Various extensions have been suggested, and, in this report, we compare their accuracy by applying them to several complex diseases.
Our results show that penalized regressions are usually robust and provide better accuracy than the existing methods for at least diseases under consideration.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Won, Sungho& Choi, Hosik& Park, Suyeon& Lee, Juyoung& Park, Changyi& Kwon, Sunghoon. 2015. Evaluation of Penalized and Nonpenalized Methods for Disease Prediction with Large-Scale Genetic Data. BioMed Research International،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1056099
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Won, Sungho…[et al.]. Evaluation of Penalized and Nonpenalized Methods for Disease Prediction with Large-Scale Genetic Data. BioMed Research International No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1056099
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Won, Sungho& Choi, Hosik& Park, Suyeon& Lee, Juyoung& Park, Changyi& Kwon, Sunghoon. Evaluation of Penalized and Nonpenalized Methods for Disease Prediction with Large-Scale Genetic Data. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1056099
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1056099
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر