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Related Concept Videos

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MicroRNA (miRNA) are short, regulatory RNA transcribed from introns—non-coding regions of a gene—or intergenic regions—stretches of DNA present between genes. Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After...
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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
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MicroRNA Databases and Tools.

Tharcísio Soares de Amorim1, Daniel Longhi Fernandes Pedro1, Alexandre Rossi Paschoal2

  • 1Department of Computer Science and Bioinformatics and Pattern Recognition Group, Universidade Tecnológica Federal do Paraná (UTFPR), Cornélio Procópio, Brazil.

Methods in Molecular Biology (Clifton, N.J.)
|August 25, 2021
PubMed
Summary
This summary is machine-generated.

This study reviews microRNA (miRNA) databases and tools for big data analysis. It provides guidance on accessing and utilizing genomic information, highlighting challenges and solutions for improved resources.

Keywords:
BioinformaticsData analysisDatabasesMirtronsPredictionRepositoryResourcesTarget geneToolsmiRNAs

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Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • Big data analytics necessitate efficient knowledge extraction from vast datasets.
  • Genomic data diversity and representation pose challenges for accurate and rapid information retrieval.
  • MicroRNAs (miRNAs) are key regulators of gene expression, discovered in the 1990s.

Purpose of the Study:

  • To explore and provide practical guidance on microRNA (miRNA) databases and tools.
  • To review existing literature and conduct an updated investigation on miRNA resources.
  • To identify challenges and propose solutions for enhancing miRNA database and tool accessibility.

Main Methods:

  • Literature review of update reviews and articles on miRNA databases and tools.
  • Updated investigation of miRNA literature, databases, and bioinformatics tools.
  • Analysis of existing resources for knowledge extraction from genomic data.

Main Results:

  • Identified key miRNA databases and tools for genomic data analysis.
  • Summarized current literature on miRNA research and resource availability.
  • Highlighted challenges in accessing and utilizing miRNA information.

Conclusions:

  • Effective utilization of miRNA databases and tools is crucial for big data analysis in genomics.
  • There is a need for improved resources and tools to overcome current challenges.
  • The study offers practical guidance and identifies future directions for miRNA resource development.