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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...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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...

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Related Experiment Video

Updated: Jul 19, 2026

An Integrated Approach for Microprotein Identification and Sequence Analysis
09:37

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

ESPERR: learning strong and weak signals in genomic sequence alignments to identify functional elements.

James Taylor1, Svitlana Tyekucheva, David C King

  • 1Center for Comparative Genomics and Bioinformatics, The Pennsylvania State University, University Park, Pennsylvania 16802, USA. james@bx.psu.edu

Genome Research
|October 21, 2006
PubMed
Summary

ESPERR (evolutionary and sequence pattern extraction through reduced representations) accurately predicts functional genomic elements using machine learning on multispecies alignments. This method enhances the identification of regulatory regions and other functional sites.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Identifying functional genomic elements is crucial for understanding gene regulation.
  • Traditional methods relying on specific sequence signals have limitations.
  • Multispecies alignments offer rich data but pose computational challenges.

Purpose of the Study:

  • To develop a computational method for improved identification of functional genomic elements.
  • To leverage multispecies alignments for capturing broader sequence and evolutionary patterns.
  • To create a predictive score for regulatory potential.

Main Methods:

  • Developed ESPERR (evolutionary and sequence pattern extraction through reduced representations), a machine learning approach.
  • Trained ESPERR on multispecies alignments to learn reduced representations.
  • Applied ESPERR to predict functional elements, including regulatory regions.

Main Results:

  • ESPERR achieved ~94% accuracy in discriminating regulatory regions from neutral sites.
  • The Regulatory Potential score captures both strong (GC content, conservation) and subtle sequence patterns.
  • ESPERR effectively predicted other functional elements like DNaseI hypersensitive sites and developmental enhancers.

Conclusions:

  • ESPERR provides a powerful and accurate method for identifying functional genomic elements.
  • The approach effectively utilizes complex patterns within multispecies alignments.
  • The software and data are publicly available for broader research application.