AIMC Topic: Open Reading Frames

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OCCAM: prediction of small ORFs in bacterial genomes by means of a target-decoy database approach and machine learning techniques.

Database : the journal of biological databases and curation
Small open reading frames (ORFs) have been systematically disregarded by automatic genome annotation. The difficulty in finding patterns in tiny sequences is the main reason that makes small ORFs to be overlooked by computational procedures. However,...

LncRNAnet: long non-coding RNA identification using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Long non-coding RNAs (lncRNAs) are important regulatory elements in biological processes. LncRNAs share similar sequence characteristics with messenger RNAs, but they play completely different roles, thus providing novel insights for biol...

A deep recurrent neural network discovers complex biological rules to decipher RNA protein-coding potential.

Nucleic acids research
The current deluge of newly identified RNA transcripts presents a singular opportunity for improved assessment of coding potential, a cornerstone of genome annotation, and for machine-driven discovery of biological knowledge. While traditional, featu...

TITER: predicting translation initiation sites by deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Translation initiation is a key step in the regulation of gene expression. In addition to the annotated translation initiation sites (TISs), the translation process may also start at multiple alternative TISs (including both AUG and non-A...