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Related Concept Videos

Protein-protein Interfaces02:04

Protein-protein Interfaces

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 polypeptide...
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

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 polypeptide...
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,...
Tagging and Fusion Proteins01:24

Tagging and Fusion Proteins

Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
Protein Complex Assembly02:41

Protein Complex Assembly

Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...

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Updated: May 26, 2026

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics
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Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics

Published on: July 6, 2014

Combining active learning and semi-supervised learning techniques to extract protein interaction sentences.

Min Song1, Hwanjo Yu, Wook-Shin Han

  • 1Information Systems Department, New Jersey Institute of Technology, University Heights, Newark, New Jersey, USA. min.song@njit.edu

BMC Bioinformatics
|December 16, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces PPISpotter, a novel method combining Active Learning (AL) and Semi-Supervised Learning (SSL) to enhance protein-protein interaction (PPI) extraction. PPISpotter significantly improves the accuracy of identifying PPIs from biomedical literature.

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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Area of Science:

  • Biomedical Informatics
  • Computational Biology
  • Natural Language Processing

Background:

  • Protein-protein interaction (PPI) extraction is crucial for biomedical research and database curation.
  • Active Learning (AL) and Semi-Supervised Support Vector Machines (SSL-SVMs) are current methods for automated PPI extraction.
  • Combining AL and SSL shows potential for improving PPI extraction performance.

Purpose of the Study:

  • To develop a novel technique for automated protein-protein interaction extraction.
  • To enhance the performance of PPI extraction by integrating Deterministic Annealing-based SSL with AL.
  • To improve SVM classifiers using comprehensive NLP-derived features.

Main Methods:

  • Proposed PPISpotter, a novel PPI extraction technique combining Deterministic Annealing-based SSL and AL.
  • Extracted comprehensive features from MEDLINE records using Natural Language Processing (NLP).
  • Incorporated syntactic, semantic, and lexical text properties into feature selection for improved SVM classification.

Main Results:

  • PPISpotter demonstrated superior performance across three PPI corpuses compared to Random Sampling, Clustering, and Transductive SVMs.
  • The system achieved significant improvements in precision, recall, and F-measure.
  • Feature selection incorporating diverse text properties boosted system performance.

Conclusions:

  • PPISpotter represents a novel, state-of-the-art technique for efficient protein-protein interaction pair extraction.
  • The combined AL and SSL approach, along with advanced feature engineering, significantly advances automated PPI extraction.