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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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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...
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The histone proteins have a flexible N-terminal tail extending out from the nucleosome. These histone tails are often subjected to post-translational modifications such as acetylation, methylation, phosphorylation, and ubiquitination. Particular combinations of these modifications form “histone codes” that influence the chromatin folding and tissue-specific gene expression.
Acetylation
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Related Experiment Video

Updated: Feb 20, 2026

Pattern-based Search of Epigenomic Data Using GeNemo
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Pattern-based Search of Epigenomic Data Using GeNemo.

Alvin Zheng1, Xiaoyi Cao1, Sheng Zhong2

  • 1Department of Bioengineering, University of California San Diego.

Journal of Visualized Experiments : Jove
|October 21, 2017
PubMed
Summary
This summary is machine-generated.

GeNemo is the first online tool for pattern-based searches of functional genomic data. It enables users to search diverse epigenomic datasets, improving data analysis and interpretation.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Epigenetics

Background:

  • Current text-based search tools for genomic data are robust, but pattern-based searches for functional genomic data are limited.
  • The exponential growth of functional genomic data necessitates advanced bioinformatic tools for analysis.

Purpose of the Study:

  • To introduce GeNemo, the first online search tool designed for pattern-based searches of functional genomic data.
  • To provide a robust platform for analyzing diverse epigenomic datasets.

Main Methods:

  • Users input functional genomic data in Browser Extensible Data (BED), Peaks, or bigWig formats.
  • Searches can be performed against various online datasets, including the Encyclopedia of DNA Elements (ENCODE) data for epigenomic marks, transcription factor binding sites, and chromatin accessibility.
  • Supports searches across different cell types, developmental stages, and species (human and mouse).

Main Results:

  • GeNemo returns a list of genomic regions with matching patterns to the input data.
  • Results can be viewed in a browser and downloaded in BED format.
  • The upgraded GeNemo features an improved graphical display and a more robust, error-resistant interface.

Conclusions:

  • GeNemo addresses the limitations in searching functional genomic data, offering a valuable tool for researchers.
  • The tool facilitates the analysis and interpretation of rapidly expanding functional genomic datasets.
  • GeNemo's improvements enhance usability and reliability for bioinformatic analyses.