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Related Concept Videos

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...
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...

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Related Experiment Video

Updated: Jun 22, 2026

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
07:55

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

Efficient exact motif discovery.

Tobias Marschall1, Sven Rahmann

  • 1Computer Science Department, Bioinformatics for High-Throughput Technologies at the Chair of Algorithm Engineering, TU Dortmund, Dortmund, Germany. tobias.marschall@tu-dortmund.de

Bioinformatics (Oxford, England)
|May 30, 2009
PubMed
Summary
This summary is machine-generated.

This study presents an exact and efficient algorithm for motif discovery in biosequences, outperforming existing methods and identifying novel motifs in Mycobacterium tuberculosis.

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Peptide-based Identification of Functional Motifs and their Binding Partners
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Peptide-based Identification of Functional Motifs and their Binding Partners

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Last Updated: Jun 22, 2026

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
07:55

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

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

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Motif discovery is crucial for sequence analysis but remains challenging due to complex search spaces and heuristic solutions.
  • Existing methods often lack exactness and efficiency, failing to guarantee optimal motif identification.

Purpose of the Study:

  • To develop an exact and efficient method for motif discovery in biosequences.
  • To address limitations of current heuristic approaches in motif identification.

Main Methods:

  • Utilized a compound Poisson approximation for motif occurrence null distribution.
  • Employed a probabilistic arithmetic automaton (PAA) for exact clump size distribution computation.
  • Developed an algorithm leveraging monotonicity properties for optimal pattern discovery.

Main Results:

  • Achieved near-exact motif discovery on IUPAC generalized string patterns.
  • Proposed two p-value scores for motif over-representation, enhancing accuracy.
  • Demonstrated a significant speedup (orders of magnitude faster) compared to exhaustive enumeration.
  • Outperformed established algorithms like MEME and Weeder on benchmark datasets.
  • Identified novel motifs in Mycobacterium tuberculosis.

Conclusions:

  • The developed method offers an exact and efficient solution to the motif discovery problem.
  • The approach significantly improves upon existing algorithms in speed and accuracy.
  • The findings have implications for identifying functional elements in biological sequences.