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 between long non-coding RNAs (lncRNAs) and protein coding transcripts (PCTs). Thus, we present a Support Vector Machine (SVM) based method to distinguish lncRNAs from PCTs, using features based on frequencies of nucleotide patterns and ORF lengths, in transcripts.

Methods

The proposed method is based on SVM and uses the first ORF relative length and frequencies of nucleotide patterns selected by PCA as features. FASTA files were used as input to calculate all possible features. These feature

SUBMITTER: Schneider HW 

PROVIDER: S-EPMC5648457 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature