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Related Concept Videos

Overview of Cell Signaling01:23

Overview of Cell Signaling

Despite the protective membrane that separates a cell from the environment, cells need the ability to detect and respond to environmental changes. Additionally, cells often need to communicate with one another. Unicellular and multicellular organisms use a variety of cell signaling mechanisms to communicate with the environment.
Cells respond to many types of information, often through receptor proteins positioned on the membrane. For example, skin cells respond to and transmit touch...
Overview of Cell Signaling01:23

Overview of Cell Signaling

Despite the protective membrane that separates a cell from the environment, cells need the ability to detect and respond to environmental changes. Additionally, cells often need to communicate with one another. Unicellular and multicellular organisms use a variety of cell signaling mechanisms to communicate with the environment.
Cells respond to many types of information, often through receptor proteins positioned on the membrane. For example, skin cells respond to and transmit touch...
Diversity in Cell Signaling Responses01:22

Diversity in Cell Signaling Responses

The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
Graded and Abrupt Responses
Some signaling systems generate...
What is Cell Signaling?02:03

What is Cell Signaling?

Despite the protective membrane that separates a cell from the environment, cells need the ability to detect and respond to environmental changes. Additionally, cells often need to communicate with one another. Unicellular and multicellular organisms use a variety of cell signaling mechanisms to communicate to respond to the environment.
What is Cell Signaling?02:03

What is Cell Signaling?

Despite the protective membrane that separates a cell from the environment, cells need the ability to detect and respond to environmental changes. Additionally, cells often need to communicate with one another. Unicellular and multicellular organisms use a variety of cell signaling mechanisms to communicate to respond to the environment.
Cell Signaling Feedback Loops01:07

Cell Signaling Feedback Loops

Positive and negative feedback loops are crucial for regulating biological signaling systems. These feedback loops are processes that connect output signals to their inputs.
Negative feedback loops
Most signaling systems have negative feedback loops that can perform different functions such as output limiter, and adaptation.
Output limiter
Upon receiving an input signal, the cellular response rapidly increases until a threshold is reached. Beyond this threshold, a negative feedback loop...

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Related Experiment Video

Updated: Jun 8, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

A comprehensive statistical model for cell signaling.

Erdem Yörük1, Michael F Ochs, Donald Geman

  • 1Department of Applied Mathematics and Statistics, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA. eyoruk1@jhu.edu

IEEE/ACM Transactions on Computational Biology and Bioinformatics
|September 22, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a novel statistical model for analyzing protein signaling networks in breast cancer. The method uses microarray data to identify specific protein abnormalities, offering potential therapeutic targets.

Related Experiment Videos

Last Updated: Jun 8, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
07:28

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

Area of Science:

  • Computational Biology
  • Systems Biology
  • Genomics

Background:

  • Protein signaling networks are crucial in cellular processes and disease development.
  • Existing statistical models for cell signaling often focus on connectivity and struggle with mammalian system complexity.
  • Limited in vivo proteomic data hinders the identification of signaling aberrations in complex organisms.

Purpose of the Study:

  • To develop a comprehensive statistical model for analyzing protein signaling networks in mammalian systems.
  • To identify individual protein abnormalities as potential therapeutic targets in diseases like breast cancer.
  • To account for cell heterogeneity and multilevel processes in signaling network analysis.

Main Methods:

  • A Bayesian network model anchored to a predefined core topology with parameter sharing.
  • Utilizing microarray data of mRNA transcripts as observable components of signaling.
  • Integrating cell-level Bayesian networks, tissue-level ensemble averages, and population-level patient differences.

Main Results:

  • The model was applied to the RAS-RAF network in a breast cancer study (118 patients).
  • Demonstrated rigorous statistical inference and reproducibility through simulations.
  • Successfully recovered receptor status from microarray data, validating the model's capability.

Conclusions:

  • The proposed statistical model offers a robust approach for dissecting complex protein signaling networks.
  • It effectively identifies potential therapeutic targets by pinpointing individual protein abnormalities.
  • The method shows promise for advancing personalized medicine in cancer treatment.