Prediction of mRNA subcellular localization using deep recurrent neural networks.

ABSTRACT:

Motivation

Messenger RNA subcellular localization mechanisms play a crucial role in post-transcriptional gene regulation. This trafficking is mediated by trans-acting RNA-binding proteins interacting with cis-regulatory elements called zipcodes. While new sequencing-based technologies allow the high-throughput identification of RNAs localized to specific subcellular compartments, the precise mechanisms at play, and their dependency on specific sequence elements, remain poorly understood.

Results

We introduce RNATracker, a novel deep neural network built to predict, from their sequence alone, the distributions of mRNA transcripts over a predefined set of subcellular compartments. RNATracker integrates several state-of-the-art deep learning techniques (e.g. CNN, LSTM and atten

SUBMITTER: Yan Z 

PROVIDER: S-EPMC6612824 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature