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 Concept Videos

You might also read

Related Articles

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

Sort by
Same author

New amino butenolides from the bulbs of Fritillaria unibracteata.

Fitoterapia·2014
Same author

[Prevalence and homology analysis on human and animals severe fever with thrombocytopenia syndrome virus infection in Yantai of Shandong province].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2014
Same author

Moderate-intensity rotating magnetic fields do not affect bone quality and bone remodeling in hindlimb suspended rats.

PloS one·2014
Same author

Databases for B-cell epitopes.

Methods in molecular biology (Clifton, N.J.)·2014
Same author

HSP60 is involved in the neuroprotective effects of naloxone.

Molecular medicine reports·2014
Same author

[Resource situation investigation about Rheum tanguticum and its sustainable utilization analysis in main production area of China].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica·2014
Same journal

DiffGRN: differential gene regulatory network analysis.

International journal of data mining and bioinformatics·2019
Same journal

Integration of multi-omics data for integrative gene regulatory network inference.

International journal of data mining and bioinformatics·2018
Same journal

The development of non-coding RNA ontology.

International journal of data mining and bioinformatics·2016
Same journal

Learning multiple distributed prototypes of semantic categories for named entity recognition.

International journal of data mining and bioinformatics·2015
Same journal

Weighted fusion regularisation and predicting microbial interactions with vector autoregressive model.

International journal of data mining and bioinformatics·2015
Same journal

Application of consensus string matching in the diagnosis of allelic heterogeneity involving transposition mutation.

International journal of data mining and bioinformatics·2015
See all related articles

Related Experiment Video

Updated: Apr 16, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

4.1K

Negative correlation based gene markers identification in integrative gene expression data.

Tao Zeng, Xuan Guo, Juan Liu

    International Journal of Data Mining and Bioinformatics
    |March 12, 2015
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces Negatively Correlated Gene Sets (NCGSs) to improve cancer prognosis accuracy. By analyzing both positive and negative gene correlations, NCGSs offer more meaningful pathogen relevance for clinical applications.

    More Related Videos

    An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
    10:17

    An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

    Published on: November 3, 2010

    23.5K
    Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
    03:37

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

    Published on: March 1, 2024

    1.5K

    Related Experiment Videos

    Last Updated: Apr 16, 2026

    Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
    05:22

    Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

    Published on: July 29, 2022

    4.1K
    An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
    10:17

    An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

    Published on: November 3, 2010

    23.5K
    Author Spotlight: Impact of Intergenic Interactions on Disease-Identifying Dark Biomarkers
    03:37

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

    Published on: March 1, 2024

    1.5K

    Area of Science:

    • Genomics
    • Translational Biomedicine
    • Bioinformatics

    Background:

    • Genetic information is increasingly used in clinical practice, particularly for cancer prognosis.
    • Current methods for cancer prognosis primarily focus on positive correlations among genes.
    • Negative gene correlations, such as negative regulation and feedback, are underutilized in cancer research.

    Purpose of the Study:

    • To propose a novel method for mining Negatively Correlated Gene Sets (NCGSs) from integrated gene expression data.
    • To enhance cancer prognosis accuracy by incorporating NCGSs alongside positively correlated gene sets.
    • To improve the pathogen relevance of gene markers identified for cancer prognosis.

    Main Methods:

    • Utilized integrative gene expression data organized as gene-time-sample or gene-sample-source data.
    • Developed methods to mine Negatively Correlated Gene Sets (NCGSs) from multiple datasets.
    • Applied NCGSs in conjunction with maximal positively correlated gene sets for prognosis classification.

    Main Results:

    • NCGSs application significantly improved cancer prognosis accuracy.
    • The inclusion of NCGSs provided more meaningful pathogen relevance for gene markers.
    • Demonstrated the utility of considering negative gene correlations in cancer prognosis models.

    Conclusions:

    • Negatively Correlated Gene Sets (NCGSs) represent a valuable addition to gene-based cancer prognosis.
    • Integrating both positive and negative gene correlations enhances the predictive power and biological relevance of cancer biomarkers.
    • This approach offers a more comprehensive analysis of gene interactions for improved clinical outcomes in oncology.