Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Identification and Functional Inference for Tumor-Associated Long Non-Coding RNA.

Ying Li, Ye He, Siyu Han

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |March 31, 2017
    PubMed
    Summary

    This study introduces a computational method to identify long non-coding RNAs (lncRNAs) linked to gastric cancer. It proposes LINC00365 as a potential biomarker for early detection, aiding in understanding gastric cancer mechanisms.

    Related Concept Videos

    You might also read

    Related Articles

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

    Sort by
    Same author

    Targeting PHKA2 by Thymol alleviates sepsis induced cardiomyocyte pyroptosis via FOXA1/KLF4-mediated macrophage polarization.

    Phytomedicine : international journal of phytotherapy and phytopharmacology·2026
    Same author

    EPHX2 Orchestrates Intestinal Epithelial Barrier Repair in Ulcerative Colitis: An Integrated Multi-Omics and Experimental Study.

    Clinical and translational science·2026
    Same author

    The Caspase-1/GSDMD/PXN/VCAM-1 Cascade Mediates Cerebral Ischemia-Reperfusion Injury.

    FASEB journal : official publication of the Federation of American Societies for Experimental Biology·2026
    Same author

    TRIM71 suppresses cervical cancer progression by inhibiting Nectin4-mediated Wnt/β-catenin signaling.

    Biology direct·2026
    Same author

    KSDiffusion: conditional diffusion for kinase-specific phosphorylation site prediction under data-limited and imbalanced regimes.

    Briefings in bioinformatics·2026
    Same author

    A masked generative graph representation learning framework empowering precise spatial domain identification.

    Bioinformatics (Oxford, England)·2026

    Area of Science:

    • Oncology
    • Genomics
    • Bioinformatics

    Background:

    • Gastric cancer is a leading cause of cancer mortality globally, particularly in China.
    • The role of long non-coding RNAs (lncRNAs) in gastric cancer pathogenesis is increasingly recognized but not fully understood.
    • Experimental methods for identifying cancer-related lncRNAs are time-consuming and costly.

    Purpose of the Study:

    • To develop a computational approach for identifying gastric cancer-associated lncRNAs.
    • To identify specific lncRNAs and their target genes as potential biomarkers for gastric cancer.
    • To explore the biological functions and molecular mechanisms of identified lncRNAs and genes in gastric cancer.

    Main Methods:

    • A computational method was developed to analyze exon-based array data for gastric cancer.

    Related Experiment Videos

  • The method reused existing gastric cancer data to identify dysregulated lncRNAs.
  • Differentially expressed genes targeted by identified lncRNAs were analyzed for potential biomarker utility.
  • Main Results:

    • A specific long non-coding RNA, LINC00365, was identified as a candidate biomarker for gastric cancer.
    • Target genes of LINC00365, with products excreted in blood, urine, or saliva, were identified.
    • These findings suggest a potential combined biomarker for gastric cancer detection.

    Conclusions:

    • The proposed computational method offers an efficient alternative to experimental approaches for identifying cancer-related lncRNAs.
    • LINC00365 and its associated excretory target genes show promise as a novel combined biomarker for gastric cancer.
    • Further investigation into the biological functions of these biomarkers can enhance understanding of gastric cancer molecular mechanisms.