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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,...
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...
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...
Intrinsically Disordered Proteins02:18

Intrinsically Disordered Proteins

Intrinsically disordered proteins are a group of proteins that do not fold into specific three-dimensional structures. Their structural flexibility allows them to complement ordered proteins to perform functions that are inaccessible to rigid structures. They are more common in eukaryotes than prokaryotes and may either be exclusively intrinsically disordered or hybrid proteins, consisting of a mix of ordered and disordered regions. The absence of a rigid structure in these proteins can be...
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.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...

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Articles linked to this work by shared authors, journal, and citation graph.

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Automated protein subfamily identification and classification.

PLoS computational biology·2007
Same author

PhyloFacts: an online structural phylogenomic encyclopedia for protein functional and structural classification.

Genome biology·2006
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Related Experiment Video

Updated: Jul 4, 2026

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web
09:51

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

Published on: July 16, 2017

Efficient functional clustering of protein sequences using the Dirichlet process.

Duncan P Brown1

  • 1Department of Bioengineering, UC Berkeley and Merck & Co, Inc, 1700 Owens St, San Francisco, CA 94158, USA. duncan_brown@merck.com

Bioinformatics (Oxford, England)
|May 31, 2008
PubMed
Summary

This study introduces a new probabilistic model for automatically clustering protein sequences into functional subfamilies. The method accurately identifies subgroups within protein families, aiding in the annotation of novel sequences.

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Area of Science:

  • Computational biology
  • Bioinformatics
  • Genomics

Background:

  • The rapid increase in genome sequencing generates numerous protein sequences lacking experimental functional data.
  • Accurate annotation of these novel protein sequences is crucial for biological research.
  • Current methods often rely on experimental evidence, which is not available for the majority of new sequences.

Purpose of the Study:

  • To develop an automated method for grouping protein sequences with similar molecular functions.
  • To create a probabilistic framework for modeling subfamilies within known protein families.
  • To enable functional annotation of protein sequences without experimental evidence.

Main Methods:

  • A novel probabilistic framework utilizing Dirichlet mixture densities.
  • Estimation of amino acid preferences within subfamily clusters.
  • Application of a Dirichlet process prior on the set of clusters.
  • Utilizing multiple sequence alignments as input.

Main Results:

  • The proposed model accurately partitions protein sequence data into functional subgroups.
  • Demonstrated effectiveness in identifying subfamilies within protein families.
  • The model successfully models subfamilies based on sequence data.

Conclusions:

  • The developed probabilistic framework provides an effective automated solution for protein sequence clustering.
  • This approach aids in the functional annotation of large-scale genomic data.
  • The method offers a valuable tool for the bioinformatics community.