Oct 25, 2018

SpliceVisuL: Visualization of Bidirectional Long Short-term Memory Networks for Splice Junction Prediction

BioRxiv : the Preprint Server for Biology
Aparajita DuttaAshish Anand

Abstract

Neural models have been able to obtain state-of-the-art performances on several genome sequence-based prediction tasks. Such models take only nucleotide sequences as input and learn relevant features on its own. However, extracting the interpretable motifs from the model remains a challenge. This work explores various existing visualization techniques in their ability to infer relevant sequence information learned by a recurrent neural network (RNN) on the task of splice junction identification. The visualization techniques have been modulated to suit the genome sequences as input. The visualizations inspect genomic regions at the level of a single nucleotide as well as a span of consecutive nucleotides. This inspection is performed based on modification of input sequences (perturbation-based) or the embedding space (back-propagation based). We infer features pertaining to both canonical and non-canonical splicing from a single neural model. Results indicate that the visualization techniques produce comparable performance for branchpoint detection. However, in case of canonical donor and acceptor junction motifs, perturbation based visualizations perform better than back-propagation based visualizations and vice-versa for non-c...Continue Reading

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Mentioned in this Paper

Biological Neural Networks
Patterns
Simonton Technique
Genome
Neural Network Simulation
Genomics
Nuclear mRNA Cis Splicing, via Spliceosome
Nucleotides
Protein Domain
RNA Splicing

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