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

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

Interactions Between Signaling Pathways

Interactions Between Signaling Pathways

Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...

You might also read

Related Articles

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

Sort by

Same author

RUVBL1 and RUVBL2 are druggable MYC effector regulators in neuroblastoma cells.

iScience·2026

Same author

Simplified mechanical organs in aquatic plants are associated with the loss of expansin genes.

Plant physiology·2026

Same author

Deconvoluting fibre type proportions from human skeletal muscle transcriptomics and proteomics data using FibeRtypeR.

The Journal of physiology·2026

Same author

Multifocal cohort analysis unveils cell types associated with regional lymph node seeding in prostate cancer.

Genome medicine·2026

Same author

Filtering for truth: high-precision taxonomic classification in nanopore shotgun metagenomics data through a KMA-based bioinformatic pipeline (KAPTAIN).

BMC genomics·2026

Same author

Experimental and numerical assessment of near-field exposure of a 60 GHZ communication antenna.

Radiation protection dosimetry·2026

Same journal

Invaders taking over-Mollusc faunal change in volcanic barrier lakes of the Albertine Rift biodiversity hotspot.

PloS one·2026

Same journal

AI-driven molecular diversification and ligand-based optimization of macitentan derivatives targeting VEGFR1 and endothelin signaling pathways.

PloS one·2026

Same journal

Performance patterns and records in the world aquatics masters championships: Where do the most frequently represented nations among the top-ten masters swimmers come from?

PloS one·2026

Same journal

Modeling diurnal Temperature-Rainfall relationships under multicollinearity using PLS-SEM: A case study of Ghana.

PloS one·2026

Same journal

Organizational culture, social capital, and emergency capacity in primary healthcare institutions: A cross-sectional structural equation modeling study comparing ordinary and older communities.

PloS one·2026

Same journal

Impact of kidney function on the metabolome in the general population.

PloS one·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 2, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Pathway Relevance Ranking for Tumor Samples through Network-Based Data Integration.

Lieven P C Verbeke¹, Jimmy Van den Eynden², Ana Carolina Fierro²

¹Department of Information Technology, Ghent University-iMinds, Ghent, Belgium.

|July 29, 2015

Summary

This summary is machine-generated.

This study introduces a novel network-based method to rank cancer pathways using multi-omics data. The approach integrates diverse data types to identify key biological pathways crucial for tumor development and patient survival.

More Related Videos

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

Published on: July 22, 2020

Related Experiment Videos

Last Updated: Jan 2, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

Published on: October 3, 2025

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

Published on: July 22, 2020

Area of Science:

Oncology
Bioinformatics
Systems Biology

Background:

Cancer is a complex, heterogeneous disease requiring integrated analysis of large multi-omics datasets.
Existing methods may not fully capture the intricate molecular landscape of cancer across different subtypes.
Simultaneous analysis of diverse tumor-related omics data is essential for a comprehensive understanding.

Purpose of the Study:

To develop and validate a novel pathway relevance ranking method for prioritizing cancer pathways.
To enable the simultaneous analysis of any combination of tumor-related omics datasets.
To identify key pathways involved in breast and ovarian cancer development and their association with patient survival.

Main Methods:

Developed a network-based pathway relevance ranking method.
Integrated gene expression, copy number, mutation, and methylation data into a comprehensive network representation.
Applied the method to breast and ovarian cancer datasets from The Cancer Genome Atlas (TCGA).

Main Results:

The method successfully identified key pathways in breast cancer, including those shared across molecular subtypes.
Demonstrated the ability to detect both universally important and subtype-specific pathways.
Analysis of ovarian cancer revealed pathways associated with patient survival, highlighting differences between good and bad outcome groups.

Conclusions:

The network-based integration of multi-omics data is crucial for understanding complex cancer biology.
The developed pathway ranking method effectively identifies key molecular pathways driving cancer development and progression.
This approach aids in uncovering the interplay of genetic and epigenetic alterations in diverse cancer subtypes and outcomes.