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Related Concept Videos

Interactions Between Signaling Pathways01:19

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...
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...
Hedgehog Signaling Pathway02:33

Hedgehog Signaling Pathway

The Hedgehog gene (Hh) was first discovered due to its control of the growth of disorganized, hair-like bristles phenotype in Drosophila, much like hedgehog spines. Hh plays a crucial role in the development of organs and the maintenance of homeostasis in both invertebrates and vertebrates. However, while Drosophila has only one Hh protein, mammals have multiple functional Hedgehog proteins - Sonic (Shh), Desert (Dhh), and Indian Hedgehog (Ihh). All of these homologous proteins have adapted to...
Hedgehog Signaling Pathway02:33

Hedgehog Signaling Pathway

The Hedgehog gene (Hh) was first discovered due to its control of the growth of disorganized, hair-like bristles phenotype in Drosophila, much like hedgehog spines. Hh plays a crucial role in the development of organs and the maintenance of homeostasis in both invertebrates and vertebrates. However, while Drosophila has only one Hh protein, mammals have multiple functional Hedgehog proteins - Sonic (Shh), Desert (Dhh), and Indian Hedgehog (Ihh). All of these homologous proteins have adapted to...
The JAK-STAT Signaling Pathway01:20

The JAK-STAT Signaling Pathway

Several cytokine receptors have tightly bound Janus kinase or JAK proteins attached at their cytosolic tail. Small signaling molecules such as cytokines, growth hormones, or prolactins bind to the cytokine receptors and initiate their dimerization. The dimerization brings the cytosolic JAKs together that trans-phosphorylate and activates each other. The activated JAKs now phosphorylate cytosolic tails of the cytokine receptors, which serve as binding sites for adaptor proteins such as  SH2...
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...

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Related Experiment Video

Updated: Jun 20, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

Predicting homologous signaling pathways using machine learning.

Babak Bostan1, Russell Greiner, Duane Szafron

  • 1Department of Computing Science, University of Alberta, Edmonton, AB T6G2E8, Canada. bioinfo@cs.ualberta.ca

Bioinformatics (Oxford, England)
|September 9, 2009
PubMed
Summary
This summary is machine-generated.

Predicting protein roles in cell signaling pathways is challenging. Our new machine learning approach, Predict Signaling Pathway (PSP), uses data from well-studied species to accurately identify protein functions in less-studied organisms.

Related Experiment Videos

Last Updated: Jun 20, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Systems Biology

Background:

  • Cell signaling pathways involve numerous proteins with specific roles crucial for cellular activity.
  • Experimentally determining the precise mapping of proteins to their roles is a complex and time-consuming process.
  • Cross-species similarities in signaling pathways offer potential for leveraging known information to understand less-studied species.

Purpose of the Study:

  • To develop an automated method for predicting the roles of proteins within cell signaling pathways.
  • To utilize conserved pathway information across species for functional annotation.
  • To address the challenges of experimental protein role determination.

Main Methods:

  • Development of an automated approach named Predict Signaling Pathway (PSP).
  • Application of machine learning techniques to build a predictive model.
  • Utilizing known signaling pathway data from well-studied species to infer roles in less-studied species.

Main Results:

  • The Predict Signaling Pathway (PSP) approach achieves a generalization F-measure of 78.2%.
  • The method was validated across 11 distinct pathways and 14 different species.
  • PSP demonstrates high effectiveness in predicting roles for proteins in pathways not yet fully studied experimentally.

Conclusions:

  • The PSP approach provides an effective computational solution for predicting protein roles in cell signaling pathways.
  • This method facilitates the understanding of cellular mechanisms in less-studied species by leveraging cross-species pathway conservation.
  • The developed tool aids in the functional annotation of proteomes, accelerating biological discovery.