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Related Concept Videos

Aggregates Classification01:29

Aggregates Classification

Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
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 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 Organization01:13

Protein Organization

Overview
Protein Organization01:24

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence.

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Related Experiment Video

Updated: Jul 18, 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

A Protein Classification Benchmark collection for machine learning.

Paolo Sonego1, Mircea Pacurar, Somdutta Dhir

  • 1Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Padriciano 99, 34012 Trieste, Italy.

Nucleic Acids Research
|December 5, 2006
PubMed
Summary

The Protein Classification Benchmark collection offers standardized datasets for comparing machine learning methods in protein classification. This resource aids researchers in evaluating algorithms for structural and functional protein annotation.

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Last Updated: Jul 18, 2026

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Machine Learning

Background:

  • Machine learning algorithms are integral to protein structural and functional annotation.
  • Standardized datasets are crucial for comparing the performance of these algorithms.

Purpose of the Study:

  • To introduce the Protein Classification Benchmark collection.
  • To provide standardized datasets for evaluating machine learning methods in protein classification.

Main Methods:

  • The collection includes datasets of protein sequences and structures.
  • Datasets are subdivided into training/test and positive/negative sets.
  • Includes distance matrices and performance measures for various classification tasks.

Main Results:

  • The collection comprises 6405 classification tasks, covering protein sequences, structures, and DNA coding regions.
  • Tasks include classification of structural domains (SCOP, CATH), functional, and taxonomic problems.
  • Hierarchical classification is supported at multiple levels.

Conclusions:

  • The Protein Classification Benchmark collection facilitates reproducible comparison of machine learning methods.
  • It serves as a valuable resource for method developers and users in the field of protein classification.