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Related Concept Videos

Protein Networks02:26

Protein Networks

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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,...
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Assembly of Signaling Complexes01:30

Assembly of Signaling Complexes

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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,...
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Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

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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...
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Protein-protein Interfaces02:04

Protein-protein Interfaces

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Amplifying Signals via Enzymatic Cascade01:22

Amplifying Signals via Enzymatic Cascade

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When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze...
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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

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Reverse phase protein arrays in signaling pathways: a data integration perspective.

Chad J Creighton1, Shixia Huang2

  • 1Department of Medicine, Baylor College of Medicine, Houston, TX, USA ; Dan L Duncan Cancer Center, Baylor College of Medicine, Houston, TX, USA.

Drug Design, Development and Therapy
|July 18, 2015
PubMed
Summary

Reverse Phase Protein Array (RPPA) provides proteomic data for signaling pathways. This review highlights RPPA

Keywords:
RPPATCGAbreast cancerintegrative analysismolecular profilingproteomics

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The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
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The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
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Area of Science:

  • Proteomics
  • Cancer Biology
  • Bioinformatics

Background:

  • Reverse Phase Protein Array (RPPA) measures protein expression, including post-translational modifications.
  • RPPA captures signaling pathway states in normal and diseased cells.
  • Integrating RPPA with other molecular data provides a comprehensive cellular profile.

Purpose of the Study:

  • To review the utility of RPPA in integrative molecular analysis.
  • To demonstrate RPPA's added value in cancer research using TCGA examples.
  • To address the need for effective visualization of complex RPPA datasets.

Main Methods:

  • Review of RPPA applications in integrative analysis.
  • Case examples from The Cancer Genome Atlas (TCGA).
  • Guidelines for visualizing complex molecular datasets, including RPPA data.

Main Results:

  • RPPA offers insights into cancer beyond other data platforms.
  • A challenge highlighted the need for RPPA data visualization methods.
  • General guidelines for effective visualization of complex molecular data were proposed.

Conclusions:

  • RPPA is a valuable tool for integrative molecular analysis in cancer research.
  • Effective visualization is crucial for interpreting complex RPPA datasets.
  • Proposed visualization principles can enhance understanding of breast cancer subtypes and large RPPA datasets.