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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...
Modern Molecular Taxonomy01:29

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Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
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.
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Conservation of Protein Domains02:26

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Signal Sequences and Sorting Receptors01:41

Signal Sequences and Sorting Receptors

Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...

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Related Experiment Video

Updated: Jun 23, 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

Factoring local sequence composition in motif significance analysis.

Patrick Ng1, Uri Keich

  • 1Department of Computer Science, Cornell University, Ithaca, NY 14853, USA.

Genome Informatics. International Conference on Genome Informatics
|May 9, 2009
PubMed
Summary

We enhanced motif finding significance analysis using local base composition. Our improved method outperforms normal approximation and enhances de novo motif discovery, outperforming existing tools on genome-wide binding data.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Motif finding is crucial for understanding gene regulation.
  • Existing significance analysis methods for motif finders often lack biological realism.
  • The normal approximation is a popular but potentially inaccurate method for assessing motif significance.

Purpose of the Study:

  • To improve the biological realism and reliability of significance analysis for motif finders.
  • To incorporate local base composition information into significance analysis.
  • To enhance de novo motif discovery using an improved significance analysis.

Main Methods:

  • Developed a biologically realistic significance analysis incorporating local base composition.
  • Utilized realistic biological data simulation for method validation.
  • Applied False Discovery Rate (FDR) analysis to real biological data.
  • Integrated the improved significance analysis into a Gibbs Sampler variant for de novo motif finding.

Main Results:

  • The new significance analysis method significantly outperforms the normal approximation.
  • The improved Gibbs Sampler variant demonstrates enhanced de novo motif discovery capabilities.
  • The enhanced motif finder achieved superior performance compared to existing tools on the Harbison genome-wide binding location dataset.

Conclusions:

  • Incorporating local base composition significantly improves motif significance analysis.
  • Reliable significance analysis is key to improving de novo motif discovery.
  • The developed method offers a more accurate and effective approach for motif discovery in genomics.