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Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

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Related Experiment Video

Updated: May 16, 2026

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
11:12

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

Published on: August 1, 2018

WEmarker: breast cancer-specific prognostic analysis with weighted multiplex network embedding.

Xingyi Li, Junming Li, Zhelin Zhao

    IEEE Transactions on Computational Biology and Bioinformatics
    |May 14, 2026
    PubMed
    Summary

    WEmarker identifies breast cancer prognostic biomarkers by analyzing gene interactions in weighted multiplex networks. This novel method reduces noise and preserves network structure, outperforming existing approaches for reliable clinical application.

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    Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
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    Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

    Published on: May 17, 2019

    Related Experiment Videos

    Last Updated: May 16, 2026

    Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
    11:12

    Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material

    Published on: August 1, 2018

    Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
    07:41

    Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

    Published on: May 17, 2019

    Area of Science:

    • Biomedical Informatics
    • Genomics
    • Cancer Research

    Background:

    • Prognostic biomarkers are crucial for tailoring breast cancer treatment post-surgery.
    • Existing network-based methods often use single networks or aggregate multiplex networks, losing structural information and failing to manage biological network noise.

    Purpose of the Study:

    • To develop a novel method, WEmarker, for breast cancer-specific prognostic biomarker identification.
    • To improve upon existing network-based approaches by addressing noise and preserving network topology.

    Main Methods:

    • WEmarker utilizes weighted multiplex networks to represent gene interactions.
    • It quantifies interaction probabilities and reduces noise in biological networks.
    • Gene nodes are represented as vectors, preserving network structure information.

    Main Results:

    • WEmarker demonstrated superior performance compared to existing methods in prognostic biomarker identification.
    • Biomarkers identified by WEmarker showed reliable biological interpretability in a case study.
    • The method effectively reduces noise and retains topological structures of biological networks.

    Conclusions:

    • WEmarker offers a robust and interpretable approach for identifying breast cancer prognostic biomarkers.
    • The method's ability to handle noise and preserve network structure makes it valuable for clinical decision-making.
    • This advancement has implications for personalized medicine in breast cancer treatment.