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Updated: Jan 30, 2026

Identification of Coding and Non-coding RNA Classes Expressed in Swine Whole Blood
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Long non-coding RNA transcriptome of uncharacterized samples can be accurately imputed using protein-coding genes.

Aritro Nath1,2, Paul Geeleher3, R Stephanie Huang1,2

  • 1Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN, USA.

Briefings in Bioinformatics
|January 19, 2019
PubMed
Summary

This study introduces the lncRNA expression imputation (LEXI) framework, enabling the characterization of long non-coding RNA (lncRNA) transcriptomes from protein-coding gene (PCG) data alone. LEXI effectively imputes missing lncRNA profiles in various tissues, advancing transcriptomic analysis.

Keywords:
GTEXTCGAexpressionimputationlncRNAmachine learning

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Long non-coding RNAs (lncRNAs) are vital gene regulators implicated in disease.
  • Existing transcriptome datasets often lack comprehensive lncRNA data compared to protein-coding genes (PCGs).

Purpose of the Study:

  • To develop a computational framework for imputing lncRNA expression profiles using PCG data.
  • To enable the characterization of lncRNA transcriptomes in samples with limited or no direct lncRNA measurements.

Main Methods:

  • Proposed the lncRNA expression imputation (LEXI) framework.
  • Utilized correlative expression patterns between lncRNAs and PCGs.
  • Compared various machine learning and missing value imputation algorithms.

Main Results:

  • Demonstrated the feasibility of imputing lncRNA transcriptomes in normal and cancer tissues.
  • LEXI successfully characterizes lncRNA profiles using only PCG expression data.
  • Identified factors influencing imputation accuracy.

Conclusions:

  • LEXI provides a robust method for reconstructing lncRNA expression profiles from PCG data.
  • This framework enhances the utility of existing transcriptome datasets for lncRNA research.
  • Offers guidelines for implementing lncRNA imputation in diverse biological contexts.