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Splice Junction Prediction in DNA Sequence Using Multilayered RNN Model

  • Rahul SarkarEmail author
  • Chandra Churh Chatterjee
  • Sayantan Das
  • Dhiman Mondal
Conference paper
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 3)

Abstract

Genes are parts of a DNA sequence responsible for protein synthesis. Splicing more specifically refers to a post-transcriptional modification that is responsible for multiple protein synthesis from a single gene. The classification of the splice junction has remained quite a challenging task in the field of bioinformatics and is equally important as the synthesized proteins are responsible for the unique characteristics observed in different living organisms. In this study, we propose a state of the art algorithm in splice junction prediction from DNA sequence using a multilayered stacked RNN model, which achieves an overall accuracy of 99.95% and an AUROC score of 1.0 for exon-intron, intron-exon as well as no-junction classification.

Keywords

Codon Exon Intron mRNA Nucleotide Splice junction Transcription 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Rahul Sarkar
    • 1
    Email author
  • Chandra Churh Chatterjee
    • 1
  • Sayantan Das
    • 2
  • Dhiman Mondal
    • 1
  1. 1.Jalpaiguri Government Engineering CollegeJalpaiguriIndia
  2. 2.Nil Ratan Sircar Medical College and HospitalKolkataIndia

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