A Support Vector Machine based method to distinguish long non-coding RNAs from protein coding transcripts

A Support Vector Machine based method to distinguish long non-coding RNAs from protein coding transcripts

Abstract Background In recent years, a rapidly increasing number of RNA transcripts has been generated by thousands of sequencing projects around the world, creating enormous volumes of transcript data to be analyzed. An important problem to be addressed when analyzing this data is distinguishing be...

Full description

Bibliographic Details
Main Authors: Hugo W. Schneider, Taina Raiol, Marcelo M. Brigido, Maria Emilia M. T. Walter, Peter F. Stadler
Format: Article
Language:English
Published: BMC 2017-10-01
Series:BMC Genomics
Subjects:
Long non-coding RNA (lncRNA)
lncRNA prediction with nucleotide pattern frequencies and ORF length
Support vector machine (SVM)
Machine learning
Principal component analysis (PCA)
Online Access:http://link.springer.com/article/10.1186/s12864-017-4178-4

Internet

http://link.springer.com/article/10.1186/s12864-017-4178-4

Similar Items