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Related Concept Videos

Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
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...
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...
Complementary DNA01:44

Complementary DNA

Overview
Complementary DNA01:44

Complementary DNA

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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

COMIT: identification of noncoding motifs under selection in coding sequences.

Deniz Kural1, Yang Ding, Jiantao Wu

  • 1Department of Biology, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, USA. kural@bc.edu

Genome Biology
|November 26, 2009
PubMed
Summary
This summary is machine-generated.

We developed the COMIT algorithm to find functional noncoding motifs within coding DNA sequences. This method reveals that nucleotide sequences often have functions beyond the proteins they encode.

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Last Updated: Jun 18, 2026

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

Published on: July 14, 2015

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Coding DNA sequences (CDS) are primarily known for encoding proteins.
  • However, noncoding elements within CDS also play crucial regulatory and functional roles.
  • These roles are often overlooked due to a focus on protein-level information.

Purpose of the Study:

  • To present the COMIT algorithm for detecting functional noncoding motifs within coding DNA.
  • To differentiate between nucleotide-level and amino acid-level effects on function.
  • To identify novel functional motifs in coding regions.

Main Methods:

  • Developed the COMIT (Coding Motif Identification Tool) algorithm.
  • Utilized sequence conservation analysis to detect motifs.
  • Explicitly separated nucleotide sequence effects from amino acid sequence effects.
  • Validated findings against diverse experimental datasets.

Main Results:

  • COMIT successfully identified known functional motifs, including splicing enhancers/silencers, replication origins, and microRNA targets.
  • The algorithm predicted numerous novel functional motifs within coding regions.
  • COMIT scores showed a strong correlation with scores not calibrated for amino acids.
  • This suggests nucleotide-level motifs frequently exert stronger functional constraints than peptide-level constraints.

Conclusions:

  • Functional noncoding motifs exist within coding DNA and can be detected computationally.
  • The COMIT algorithm provides a robust method for identifying these motifs.
  • Nucleotide sequence composition can be a primary driver of function, sometimes overriding protein-level constraints.