Identification of long non-coding transcripts with feature selection: a comparative study.

ABSTRACT:

Background

The unveiling of long non-coding RNAs as important gene regulators in many biological contexts has increased the demand for efficient and robust computational methods to identify novel long non-coding RNAs from transcripts assembled with high throughput RNA-seq data. Several classes of sequence-based features have been proposed to distinguish between coding and non-coding transcripts. Among them, open reading frame, conservation scores, nucleotide arrangements, and RNA secondary structure have been used with success in literature to recognize intergenic long non-coding RNAs, a particular subclass of non-coding RNAs.

Results

In this paper we perform a systematic assessment of a wide collection of features extracted from sequence data. We use most of the features pr

SUBMITTER: Ventola GM 

PROVIDER: S-EPMC5364679 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature