Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees
المؤلفون المشاركون
Williams, Philip H.
Weiller, Georg
Eyles, Rod
المصدر
العدد
المجلد 2012، العدد 2012 (31 ديسمبر/كانون الأول 2012)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2012-11-07
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
MicroRNAs (miRNAs) are nonprotein coding RNAs between 20 and 22 nucleotides long that attenuate protein production.
Different types of sequence data are being investigated for novel miRNAs, including genomic and transcriptomic sequences.
A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences.
MirTools, mirDeep2, and miRanalyzer require “read count” to be included with the input sequences, which restricts their use to deep-sequencing data.
Our aim was to train a predictor using a cross-section of different species to accurately predict miRNAs outside the training set.
We wanted a system that did not require read-count for prediction and could therefore be applied to short sequences extracted from genomic, EST, or RNA-seq sources.
A miRNA-predictive decision-tree model has been developed by supervised machine learning.
It only requires that the corresponding genome or transcriptome is available within a sequence window that includes the precursor candidate so that the required sequence features can be collected.
Some of the most critical features for training the predictor are the miRNA:miRNA∗ duplex energy and the number of mismatches in the duplex.
We present a cross-species plant miRNA predictor with 84.08% sensitivity and 98.53% specificity based on rigorous testing by leave-one-out validation.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Williams, Philip H.& Eyles, Rod& Weiller, Georg. 2012. Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees. Journal of Nucleic Acids،Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-488494
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Williams, Philip H.…[et al.]. Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees. Journal of Nucleic Acids No. 2012 (2012), pp.1-10.
https://search.emarefa.net/detail/BIM-488494
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Williams, Philip H.& Eyles, Rod& Weiller, Georg. Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees. Journal of Nucleic Acids. 2012. Vol. 2012, no. 2012, pp.1-10.
https://search.emarefa.net/detail/BIM-488494
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-488494
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