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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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Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

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Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order...
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Related Experiment Video

Updated: Jun 14, 2025

Unravelling the Function of a Bacterial Effector from a Non-cultivable Plant Pathogen Using a Yeast Two-hybrid Screen
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Unravelling the Function of a Bacterial Effector from a Non-cultivable Plant Pathogen Using a Yeast Two-hybrid Screen

Published on: January 20, 2017

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Fungtion: A Server for Predicting and Visualizing Fungal Effector Proteins.

Jiahui Li1, Jinzheng Ren2, Wei Dai1

  • 1Biomedicine Discovery Institute, Monash University, VIC 3800, Australia; Centre to Impact AMR, Monash University, VIC 3800, Australia.

Journal of Molecular Biology
|September 5, 2024
PubMed
Summary
This summary is machine-generated.

Fungtion is a new toolkit that accurately predicts fungal effectors, which are proteins secreted by fungi to manipulate plant defenses. This tool aids in discovering effector functions and understanding plant-pathogen interactions.

Keywords:
fungal effector predictionmachine learningpre-trained protein language modelsprotein sequence analysisweb server

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Live-cell Imaging of Fungal Cells to Investigate Modes of Entry and Subcellular Localization of Antifungal Plant Defensins
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Last Updated: Jun 14, 2025

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Live-cell Imaging of Fungal Cells to Investigate Modes of Entry and Subcellular Localization of Antifungal Plant Defensins
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Live-cell Imaging of Fungal Cells to Investigate Modes of Entry and Subcellular Localization of Antifungal Plant Defensins

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Area of Science:

  • Plant pathology
  • Mycology
  • Bioinformatics

Background:

  • Fungal pathogens threaten plant health by secreting effector proteins.
  • Identifying these effectors is difficult due to a lack of conserved sequence motifs.

Purpose of the Study:

  • Introduce Fungtion, a novel toolkit for predicting and visualizing fungal effectors.
  • Facilitate the discovery, annotation, and hypothesis generation of effector functions.

Main Methods:

  • Developed a hybrid framework combining protein language models and known effector data.
  • Implemented state-of-the-art prediction algorithms.
  • Created interactive visualizations for exploring effector relationships.

Main Results:

  • Achieved state-of-the-art prediction performance for fungal effectors.
  • Enabled exploration of sequence- and high-level relationships between predicted and known effectors.
  • Provided a valuable resource for biological and computational research.

Conclusions:

  • Fungtion is a powerful tool for identifying fungal effectors and understanding plant-pathogen interactions.
  • The toolkit supports deeper insights into fungal effector functions.
  • It serves as a resource for developing future effector prediction methodologies.