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Related Concept Videos

MicroRNAs

MicroRNAs

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 the pre-miRNA...

MicroRNAs

MicroRNAs

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 the pre-miRNA ends...

MicroRNAs

MicroRNAs

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 the pre-miRNA ends...

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Small interfering RNAs (siRNA)

Small interfering RNAs, or siRNAs, are short regulatory RNA molecules that can silence genes post-transcriptionally, as well as the transcriptional level in some cases. siRNAs are important for protecting cells against viral infections and silencing transposable genetic elements.
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Related Experiment Video

Updated: May 29, 2026

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Published on: June 12, 2018

OMIT: a domain-specific knowledge base for microRNA target prediction.

Jingshan Huang¹, Christopher Townsend, Dejing Dou

¹School of Computer and Information Sciences, University of South Alabama, 307 University Blvd. N, Mobile, Alabama, USA. huang@usouthal.edu

Pharmaceutical Research

|September 1, 2011

Summary

Predicting microRNA target genes in human cancer is challenging. The Ontology for MicroRNA Targets (OMIT) knowledge base streamlines this process, aiding cancer research and clinical decisions.

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Identifying Targets of Human microRNAs with the LightSwitch Luciferase Assay System using 3'UTR-reporter Constructs and a microRNA Mimic in Adherent Cells

Published on: September 28, 2011

Related Experiment Videos

Last Updated: May 29, 2026

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Biotin-based Pulldown Assay to Validate mRNA Targets of Cellular miRNAs

Published on: June 12, 2018

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

Published on: April 6, 2012

Identifying Targets of Human microRNAs with the LightSwitch Luciferase Assay System using 3'UTR-reporter Constructs and a microRNA Mimic in Adherent Cells

Identifying Targets of Human microRNAs with the LightSwitch Luciferase Assay System using 3'UTR-reporter Constructs and a microRNA Mimic in Adherent Cells

Published on: September 28, 2011

Area of Science:

Bioinformatics
Genomics
Cancer Biology

Background:

MicroRNAs (miRNAs) play crucial roles in human cancer, but predicting their target genes is difficult.
Current prediction methods are inefficient, error-prone, and rely heavily on limited prior biological knowledge.
Accurate miRNA target gene identification is vital for understanding cancer mechanisms and developing therapies.

Purpose of the Study:

To develop a novel knowledge base for facilitating microRNA target gene prediction.
To address the limitations of existing time-consuming and error-prone prediction methods.
To support cancer researchers and clinicians in their work with miRNAs.

Main Methods:

Designed a domain-specific knowledge base using the Ontology for MicroRNA Targets (OMIT).
Implemented semantic annotation and data integration strategies within the OMIT system.
Developed a user-friendly interface for accessing and utilizing the knowledge base.

Main Results:

The OMIT system provides a structured and integrated knowledge base for miRNA target prediction.
The ontology design and semantic annotation facilitate efficient knowledge acquisition.
The user-friendly interface enhances accessibility for biologists.

Conclusions:

The OMIT system effectively assists biologists in predicting miRNA target genes in human cancer.
This tool aids in unraveling the complex roles of miRNAs in oncogenesis.
OMIT can contribute to informed clinical decision-making for cancer patient treatment.