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A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA
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Exon Mapping in Long Noncoding RNAs Using Digital Filters.

Tina P George1, Tessamma Thomas1

  • 1Department of Electronics, Cochin University of Science and Technology (CUSAT), Kochi, India.

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|October 10, 2017
PubMed
Summary
This summary is machine-generated.

This study maps exons in long noncoding RNAs (lncRNAs) using digital filters and wavelet transforms. The findings aid in understanding lncRNA function and potential coding capacity.

Keywords:
DSP methodsDWT denoisingLong noncoding RNAantinotch filterdigital filter bankexon prediction

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Long noncoding RNAs (lncRNAs) were once considered transcriptional noise but are now recognized for crucial roles in biological regulation.
  • lncRNAs are increasingly implicated in diverse developmental processes and various human diseases.

Purpose of the Study:

  • To develop and apply digital filtering techniques for accurate exon mapping of human lncRNA sequences.
  • To analyze lncRNA sequences for G-C concentration and identify potential coding regions indicated by START and STOP codons.

Main Methods:

  • Exon mapping of human lncRNA sequences from NCBI GenBank using antinotch digital filters.
  • Application of the period 3 property, a known exon indicator, for sequence analysis.
  • Utilizing discrete wavelet transform filter banks to refine exon plots by reducing spectral noise.

Main Results:

  • Accurate exon locations were predicted, conforming to specified ranges in GenBank.
  • Analysis revealed G-C concentrations within the lncRNA sequences.
  • Identification of START and STOP codons, suggesting potential coding capabilities for some lncRNAs.

Conclusions:

  • The applied digital filtering and wavelet transform methods provide a robust approach for lncRNA exon prediction.
  • The findings contribute to a deeper understanding of lncRNA structure and potential functional roles.
  • This analysis advances the study of lncRNAs in both normal biological processes and disease states.