Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Spectral CT-based habitat analysis for predicting pathologic response to neoadjuvant therapy in gastric cancer.

European radiology·2026

Same author

Ferrostatin-1 inhibits ferroptosis and alleviates organophosphate nerve agent-induced cognitive deficits by regulating ACSL4/GPX4 and NCOA4/FTH1 pathways in the hippocampus of guinea pigs.

Ecotoxicology and environmental safety·2026

Same author

Correction: Time-dependent diffusion MRI for noninvasive molecular subtype differentiation and biological correlation in breast cancer: emphasizing the emerging three-tier HER2 classification.

Frontiers in oncology·2026

Same author

SSGJ-608 in moderate-to-severe plaque psoriasis: a multicenter, randomized, open-label, phase 3 study.

Frontiers in immunology·2026

Same author

Noninvasive identification of proliferative hepatocellular carcinoma based on CEUS quantitative morphological feature.

European journal of radiology·2026

Same author

The atlas of abdominal organ remodeling in hepatocellular carcinoma patients: An artificial intelligence-based multicenter imaging study.

Med (New York, N.Y.)·2026

Search research articles

Related Experiment Video

Updated: Oct 11, 2025

Lung microRNA Profiling Across the Estrous Cycle in Ozone-exposed Mice

Lung microRNA Profiling Across the Estrous Cycle in Ozone-exposed Mice

Published on: January 7, 2019

ISFMDA: Learning Interactions of Selected Features-Based Method for Predicting Potential MicroRNA-Disease

Xuejun Chen¹, Zhenran Jiang¹

¹School of Computer Science and Technology, East China Normal University, Shanghai, China.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology

|December 1, 2021

Summary

This summary is machine-generated.

This study introduces ISFMDA, a new computational method for predicting microRNA-disease associations. The algorithm effectively identifies key features, improving prediction accuracy for this important bioinformatics task.

Keywords:

deep neural network extreme gradient boosting factorization machine miRNA-disease associations recursive feature elimination

More Related Videos

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Published on: May 25, 2015

Related Experiment Videos

Last Updated: Oct 11, 2025

Lung microRNA Profiling Across the Estrous Cycle in Ozone-exposed Mice

Lung microRNA Profiling Across the Estrous Cycle in Ozone-exposed Mice

Published on: January 7, 2019

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers

Published on: March 1, 2024

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Published on: May 25, 2015

Area of Science:

Computational Biology
Bioinformatics
Genomics

Background:

Predicting microRNA-disease associations is crucial in computational biology.
Improving prediction performance relies on mining sophisticated features.

Purpose of the Study:

To propose a novel algorithm, ISFMDA, for predicting microRNA-disease associations.
To effectively learn feature interactions for enhanced prediction accuracy.

Main Methods:

ISFMDA utilizes recursive feature elimination.
It employs extreme gradient boosting, a factorization machine, and a deep neural network.
The algorithm learns low- or high-order interactions of selected features.

Main Results:

ISFMDA achieved an Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.9342 ± 0.0007.
This was demonstrated through fivefold cross-validation.
The method utilized only 51.25% of the original features, confirming its efficiency.

Conclusions:

The proposed ISFMDA algorithm is effective for predicting microRNA-disease associations.
The integration of advanced machine learning techniques enhances feature interaction learning.
This approach offers a promising direction for computational disease association studies.