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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...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
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...
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...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...

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Related Experiment Video

Updated: Jul 2, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

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

Published on: July 14, 2015

Efficient constrained multiple sequence alignment with performance guarantee.

Francis Y L Chin1, N L Ho, T W Lam

  • 1Department of Computer Science, The University of Hong Kong, Pokfulum Road, Hong Kong, China. chin@cs.hku.hk

Journal of Bioinformatics and Computational Biology
|March 8, 2005
PubMed
Summary
This summary is machine-generated.

New algorithms for constrained multiple sequence alignment improve efficiency and space requirements. These methods offer a worst-case guarantee on alignment quality, making them more practical for real-world data.

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Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

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Related Experiment Videos

Last Updated: Jul 2, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
07:08

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

Published on: July 14, 2015

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
16:02

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation

Published on: February 10, 2023

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Algorithm Design

Background:

  • Constrained multiple sequence alignment is crucial for understanding sequence structure.
  • Previous algorithms often require excessive memory (O(n^4) space), limiting their applicability.

Purpose of the Study:

  • To develop novel algorithms for constrained multiple sequence alignment.
  • To enhance efficiency in terms of time and space complexity.
  • To provide a worst-case guarantee on alignment quality.

Main Methods:

  • Development of new algorithmic approaches for constrained sequence alignment.
  • Focus on reducing space complexity by a quadratic factor.
  • Empirical validation using real biological datasets.

Main Results:

  • The new algorithms demonstrate superior time and space efficiency compared to existing methods.
  • Significant reduction in memory requirements, overcoming limitations of previous O(n^4)-space algorithms.
  • Experimental results confirm improvements in both alignment quality and resource utilization.

Conclusions:

  • The presented algorithms offer a more efficient and practical solution for constrained multiple sequence alignment.
  • The reduced space complexity makes these algorithms suitable for larger datasets and complex structural constraints.
  • These advancements contribute to improved sequence analysis in bioinformatics.