Determining Cutoff Point of Ensemble Trees Based on Sample Size in Predicting Clinical Dose with DNA Microarray Data
المؤلفون المشاركون
Karabulut, Erdem
Yılmaz Isıkhan, Selen
Alpar, Celal Reha
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-12-20
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Background/Aim.
Evaluating the success of dose prediction based on genetic or clinical data has substantially advanced recently.
The aim of this study is to predict various clinical dose values from DNA gene expression datasets using data mining techniques.
Materials and Methods.
Eleven real gene expression datasets containing dose values were included.
First, important genes for dose prediction were selected using iterative sure independence screening.
Then, the performances of regression trees (RTs), support vector regression (SVR), RT bagging, SVR bagging, and RT boosting were examined.
Results.
The results demonstrated that a regression-based feature selection method substantially reduced the number of irrelevant genes from raw datasets.
Overall, the best prediction performance in nine of 11 datasets was achieved using SVR; the second most accurate performance was provided using a gradient-boosting machine (GBM).
Conclusion.
Analysis of various dose values based on microarray gene expression data identified common genes found in our study and the referenced studies.
According to our findings, SVR and GBM can be good predictors of dose-gene datasets.
Another result of the study was to identify the sample size of n=25 as a cutoff point for RT bagging to outperform a single RT.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yılmaz Isıkhan, Selen& Karabulut, Erdem& Alpar, Celal Reha. 2016. Determining Cutoff Point of Ensemble Trees Based on Sample Size in Predicting Clinical Dose with DNA Microarray Data. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1100174
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yılmaz Isıkhan, Selen…[et al.]. Determining Cutoff Point of Ensemble Trees Based on Sample Size in Predicting Clinical Dose with DNA Microarray Data. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1100174
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yılmaz Isıkhan, Selen& Karabulut, Erdem& Alpar, Celal Reha. Determining Cutoff Point of Ensemble Trees Based on Sample Size in Predicting Clinical Dose with DNA Microarray Data. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1100174
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1100174
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