A Systematic Evaluation of Feature Selection and Classification Algorithms Using Simulated and Real miRNA Sequencing Data
المؤلفون المشاركون
Yang, Sheng
Guo, Li
Shao, Fang
Zhao, Yang
Chen, Feng
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-10-05
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Sequencing is widely used to discover associations between microRNAs (miRNAs) and diseases.
However, the negative binomial distribution (NB) and high dimensionality of data obtained using sequencing can lead to low-power results and low reproducibility.
Several statistical learning algorithms have been proposed to address sequencing data, and although evaluation of these methods is essential, such studies are relatively rare.
The performance of seven feature selection (FS) algorithms, including baySeq, DESeq, edgeR, the rank sum test, lasso, particle swarm optimistic decision tree, and random forest (RF), was compared by simulation under different conditions based on the difference of the mean, the dispersion parameter of the NB, and the signal to noise ratio.
Real data were used to evaluate the performance of RF, logistic regression, and support vector machine.
Based on the simulation and real data, we discuss the behaviour of the FS and classification algorithms.
The Apriori algorithm identified frequent item sets (mir-133a, mir-133b, mir-183, mir-937, and mir-96) from among the deregulated miRNAs of six datasets from The Cancer Genomics Atlas.
Taking these findings altogether and considering computational memory requirements, we propose a strategy that combines edgeR and DESeq for large sample sizes.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yang, Sheng& Guo, Li& Shao, Fang& Zhao, Yang& Chen, Feng. 2015. A Systematic Evaluation of Feature Selection and Classification Algorithms Using Simulated and Real miRNA Sequencing Data. Computational and Mathematical Methods in Medicine،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1057823
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yang, Sheng…[et al.]. A Systematic Evaluation of Feature Selection and Classification Algorithms Using Simulated and Real miRNA Sequencing Data. Computational and Mathematical Methods in Medicine No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1057823
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yang, Sheng& Guo, Li& Shao, Fang& Zhao, Yang& Chen, Feng. A Systematic Evaluation of Feature Selection and Classification Algorithms Using Simulated and Real miRNA Sequencing Data. Computational and Mathematical Methods in Medicine. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1057823
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1057823
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