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Updated: Feb 23, 2026

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BUFET: boosting the unbiased miRNA functional enrichment analysis using bitsets.

Konstantinos Zagganas1,2, Thanasis Vergoulis3, Maria D Paraskevopoulou4,5

  • 1University of Peloponnese, Department of Informatics and Telecommunications, Tripoli, 22100, Greece. kzagganas@uop.gr.

BMC Bioinformatics
|September 7, 2017
PubMed
Summary
This summary is machine-generated.

We developed BUFET, a faster method for analyzing microRNA (miRNA) gene regulation. This computational approach significantly speeds up predicting biological processes targeted by miRNAs, making analysis more efficient.

Keywords:
BUFETFunctional enrichment analysismiRNAs

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • MicroRNAs (miRNAs) regulate biological processes by targeting genes.
  • Unbiased miRNA functional enrichment analysis is a precise in silico method for predicting miRNA-regulated processes.
  • Current methods are computationally intensive and costly.

Purpose of the Study:

  • To introduce BUFET, a novel approach to accelerate unbiased miRNA functional enrichment analysis.
  • To improve the computational efficiency of predicting miRNA-gene interactions and regulated biological pathways.

Main Methods:

  • Utilizing efficient bitset-based algorithms.
  • Implementing parallel computation techniques for enhanced performance.
  • Benchmarking against state-of-the-art implementations.

Main Results:

  • BUFET significantly reduces execution time for unbiased miRNA functional enrichment analysis.
  • The approach demonstrates superior computational efficiency compared to existing methods.
  • Performance gains are observed across both single- and multi-core scenarios.

Conclusions:

  • BUFET offers a substantial speed improvement for miRNA functional enrichment analysis.
  • The method is more than an order of magnitude faster than current tools in certain cases.
  • BUFET enhances the feasibility of large-scale miRNA target prediction and pathway analysis.