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Related Concept Videos

IP3/DAG Signaling Pathway01:11

IP3/DAG Signaling Pathway

Membrane lipids such as phosphatidylinositol (PI) are precursors for several membrane-bound and soluble second messengers. Specific kinases phosphorylate PI and produce phosphorylated inositol phospholipids. One such inositol phospholipids are the  phosphatidylinositol-4,5 bisphosphate [PI(4,5)P2], present in the inner half of the lipid bilayer. Upon ligand binding, GPCR stimulates Gq proteins to turn on phospholipase Cꞵ. Activated phospholipase Cꞵ cleaves PI(4,5)P2 and produces two-second...
Assembly of Signaling Complexes01:30

Assembly of Signaling Complexes

Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
Interaction domains in cell signaling
Interaction domains recognize exposed features of their binding partners containing post-translationally modified sequences,...
Conservation of Protein Domains02:26

Conservation of Protein Domains

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Membrane Domains01:18

Membrane Domains

The membrane domains concentrate specific lipids and proteins at one place within the membrane, which helps in cell signaling, adhesion, and other critical cellular processes. These domains can differ in size, composition, function, and lifespan.
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The membrane comprises a group of distinct proteins responsible for carrying out a cell's specific function. For example, the plasma membrane of the human sperm, or a single germ cell, contains a unique set of proteins in the anterior...
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

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Related Experiment Video

Updated: Jul 3, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
07:15

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

Predicting pathway membership via domain signatures.

Holger Fröhlich1, Mark Fellmann, Holger Sültmann

  • 1German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. h.froehlich@dkfz-heidelberg.de

Bioinformatics (Oxford, England)
|August 5, 2008
PubMed
Summary

Predicting gene-to-pathway mapping is crucial for understanding cellular processes. Our model uses protein domain signatures to accurately map genes to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, improving functional gene characterization.

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A Protocol for Computer-Based Protein Structure and Function Prediction
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A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

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Last Updated: Jul 3, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
07:15

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Published on: January 16, 2019

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Functional gene characterization is vital for understanding cellular processes.
  • Pathway databases like KEGG offer valuable gene information, but coverage is limited.
  • Protein domain information, available from databases like InterPro, covers a larger gene set.

Purpose of the Study:

  • To develop a classification model for predicting gene-to-KEGG pathway mapping using protein domain signatures.
  • To leverage the hierarchical structure of KEGG pathways and account for multi-pathway gene memberships.
  • To enhance the functional annotation of genes with limited existing pathway data.

Main Methods:

  • A classification model combining Support Vector Machine (SVM) and ranking perceptron approaches.
  • Utilizing gene domain signatures as input features for the classification model.
  • Scoring potential gene mappings across the KEGG pathway hierarchy.

Main Results:

  • The developed model demonstrates high prediction performance for gene-to-KEGG pathway mapping.
  • The model effectively utilizes the hierarchical organization of KEGG pathways.
  • Accurate prediction of membership to individual pathway components was achieved, particularly for signaling pathways.

Conclusions:

  • Protein domain signatures can effectively predict gene-to-KEGG pathway mappings.
  • The developed classification model improves functional gene characterization by assigning genes to relevant pathways.
  • This approach enhances the utility of pathway databases for biological research.