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Related Concept Videos

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.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...
Prokaryotic vs. Eukaryotic Cells01:28

Prokaryotic vs. Eukaryotic Cells

Prokaryotic and eukaryotic cells represent two fundamental types of cellular organization, differing significantly in structure, complexity, and function. These distinctions underpin the biological diversity seen across domains of life.Prokaryotic Cell CharacteristicsProkaryotic cells, exemplified by bacteria and archaea, are structurally simple and lack membrane-bound organelles, including a nucleus. Their genetic material consists of a single, circular DNA molecule in the nucleoid region,...
Protein Networks02:26

Protein Networks

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,...
Protein Networks02:26

Protein Networks

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,...
Overview of Protein Sorting and Transport01:45

Overview of Protein Sorting and Transport

Eukaryotic cells have different membrane-bound organelles with distinct protein requirements. The process by which proteins are targeted to a specific organelle is called protein sorting.
Protein sorting can be of two types: signal-based sorting and vesicle-based trafficking. In signal-based sorting, specific amino acid sequences called sorting signals target proteins to the proper location inside the cell either via gated transport or by protein translocation.  In gated transport, folded...
Eukaryotic Compartmentalizations01:46

Eukaryotic Compartmentalizations

One of the distinguishing features of eukaryotic cells is that they contain membrane-bound organelles, such as the nucleus and mitochondria, that carry out specialized functions. Since biological membranes are only selectively permeable to solutes, they help create a compartment with controlled conditions inside an organelle. These microenvironments are tailored to the organelle's specific functions and help isolate them from the surrounding cytosol.
For example, lysosomes in the animal cells...

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Related Experiment Video

Updated: Jul 17, 2026

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry
14:58

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Published on: November 12, 2012

Euk-PLoc: an ensemble classifier for large-scale eukaryotic protein subcellular location prediction.

H-B Shen1, J Yang, K-C Chou

  • 1Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China.

Amino Acids
|January 20, 2007
PubMed
Summary

A new computational tool, Euk-PLoc, accurately predicts eukaryotic protein subcellular locations using an ensemble classifier. This method improves accuracy for proteins lacking homology, aiding in understanding cellular functions and networks.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Cell Biology

Background:

  • The post-genomic era presents a challenge in identifying the subcellular locations of numerous new protein sequences.
  • Accurate subcellular localization is crucial for understanding protein function, interactions, and cellular networking.
  • Predicting eukaryotic protein localization is complex, especially for proteins with low homology to known ones or requiring coverage of multiple locations.

Purpose of the Study:

  • To develop an automated, fast, and reliable method for predicting the subcellular locations of eukaryotic proteins.
  • To address the challenge of predicting localization for proteins with limited homology and a broad range of potential locations.
  • To create a novel predictor that overcomes homology bias and improves prediction accuracy.

Main Methods:

  • Formulated protein samples by hybridizing Gene Ontology database information with amphiphilic pseudo amino acid composition.
  • Developed a novel ensemble hybridization classifier by fusing multiple K-Nearest Neighbor (KNN) based classifiers using a voting system.
  • Constructed a benchmark dataset covering 18 distinct subcellular localizations, ensuring no proteins shared >=25% sequence identity within the same location.

Main Results:

  • Achieved overall success rates of 81.6% (5-fold cross-validation) and 80.3% (jackknife test) on a stringent benchmark dataset.
  • Demonstrated a 40-50% improvement in accuracy compared to existing methods on the same dataset.
  • The predictor, Euk-PLoc, is available as a web server, with downloadable predictions for Swiss-Prot entries lacking clear localization data.

Conclusions:

  • The developed Euk-PLoc predictor offers a powerful and accurate solution for eukaryotic protein subcellular localization.
  • The ensemble hybridization approach effectively overcomes homology bias and enhances prediction performance.
  • Euk-PLoc provides valuable resources for researchers by offering predictions for unannotated or uncertain protein entries, aiding functional and network studies.