Sequence Motif-Based One-Class Classifiers Can Achieve Comparable Accuracy to Two-Class Learners for Plant microRNA Detection
نویسندگان
چکیده
منابع مشابه
Sequence Motif-Based One-Class Classifiers Can Achieve Comparable Accuracy to Two-Class Learners for Plant microRNA Detection
microRNAs (miRNAs) are short nucleotide sequences expressed by a genome that are involved in post transcriptional modulation of gene expression. Since miRNAs need to be co-expressed with their target mRNA to observe an effect and since miRNAs and target interactions can be cooperative, it is currently not possible to develop a comprehensive experimental atlas of miRNAs and their targets. To ove...
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The application of one-class machine learning is gaining attention in the computational biology community. Different studies have described the use of two-class machine learning to predict microRNAs (miRNAs) gene target. Most of these methods require the generation of an artificial negative class. However, designation of the negative class can be problematic and if it is not properly done can a...
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ژورنال
عنوان ژورنال: Journal of Biomedical Science and Engineering
سال: 2015
ISSN: 1937-6871,1937-688X
DOI: 10.4236/jbise.2015.810065