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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...
Protein Families02:47

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key locations, protein...
Protein Families02:47

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism.   Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members.   If these new proteins contain similar amino acids in key locations, protein...
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...
Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved DNA...
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,...

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Related Experiment Video

Updated: Jun 12, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Discovering interesting motif-sets for multi-class protein sequence classification.

Patrick C H Ma1, Keith C C Chan

  • 1Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China. pch_ma@alumni.polyu.edu.hk

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|May 27, 2010
PubMed
Summary
This summary is machine-generated.

This study introduces a novel data mining technique for protein sequence classification. It effectively identifies biologically meaningful motifs to accurately categorize proteins into functional families.

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Last Updated: Jun 12, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Peptide-based Identification of Functional Motifs and their Binding Partners
14:28

Peptide-based Identification of Functional Motifs and their Binding Partners

Published on: June 30, 2013

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Protein sequence classification is crucial for understanding biological function.
  • Existing methods may lack the precision needed for accurate multi-class classification.
  • Identifying conserved motifs is key to distinguishing protein families.

Purpose of the Study:

  • To develop an effective data mining technique for multi-class protein sequence classification.
  • To discover discriminative motif-sets for accurate protein family identification.
  • To improve upon existing protein sequence classification methods.

Main Methods:

  • A two-phase approach utilizing the MEME (Multiple Expectation Maximization for Motif Elicitation) algorithm.
  • Phase 1: Discovery of highly conserved motifs within protein families.
  • Phase 2: Pattern discovery to identify classification-specific motif-sets for a single classifier.

Main Results:

  • The proposed technique effectively classifies proteins into their corresponding functional families.
  • Experimental results demonstrate superior performance compared to existing protein sequence classifiers.
  • Discovered motif-sets were found to be biologically meaningful, aiding interpretation.

Conclusions:

  • The developed data mining technique offers an effective solution for multi-class protein sequence classification.
  • The method successfully identifies biologically relevant motifs for accurate functional family assignment.
  • This approach enhances the capability of classifying and understanding protein functions.