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Related Concept Videos

Epigenetic Regulation01:37

Epigenetic Regulation

Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
X-chromosome...
Epigenetic Regulation01:46

Epigenetic Regulation

Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
Epigenetic Regulation01:46

Epigenetic Regulation

Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
Riboswitches01:56

Riboswitches

Riboswitches are non-coding mRNA domains that regulate the transcription and translation of downstream genes without the help of proteins. Riboswitches bind directly to a metabolite and can form unique stem-loop or hairpin structures in response to the amount of the metabolite present. They have two distinct regions – a metabolite-binding aptamer and an expression platform.
The aptamer has high specificity for a particular metabolite which allows riboswitches to specifically regulate...
Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the addition of a...

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Related Experiment Video

Updated: May 7, 2026

An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations
11:36

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A wavelet-based method to exploit epigenomic language in the regulatory region.

Nha Nguyen1, An Vo, Kyoung-Jae Won

  • 1Department of Genetics, Institute for Diabetes, Obesity and Metabolism, School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA and Center for Neurosciences, The Feinstein Institute for Medical Research, Manhasset, NY 11030, USA.

Bioinformatics (Oxford, England)
|October 8, 2013
PubMed
Summary
This summary is machine-generated.

We developed AWNFR, a novel computational method to classify epigenomic landscapes and identify regulatory regions. AWNFR accurately detects histone modification patterns, improving our understanding of gene regulation.

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Area of Science:

  • Genomics
  • Computational Biology
  • Bioinformatics

Background:

  • Epigenetic landscapes in regulatory regions reveal transcription factor binding.
  • Understanding epigenetic variation is key for condition-specific gene regulation.
  • Advanced computational methods are needed for complex epigenetic data analysis.

Purpose of the Study:

  • To develop a computational method for classifying epigenomic landscapes.
  • To identify regulatory regions based on epigenetic patterns.
  • To analyze epigenomic variation and codes.

Main Methods:

  • Developed AWNFR (Wavelet-based Nucleosome Footprint Recognition) method.
  • Utilized mixture of Gaussians to model nucleosome shape.
  • Employed down-sampling and wavelet footprint for accuracy and speed.
  • Applied method to epigenome data from mouse embryonic stem cells and human lung fibroblast cells (IMR90).

Main Results:

  • AWNFR effectively classifies epigenomic landscapes and identifies regulatory regions.
  • The method demonstrates superior accuracy and efficiency compared to existing approaches.
  • AWNFR successfully identifies co-occurring histone marks and captures epigenomic variation over time.

Conclusions:

  • AWNFR provides an effective computational approach for analyzing epigenomic landscapes.
  • The method enhances the identification of regulatory elements and understanding of gene regulation.
  • AWNFR facilitates the study of dynamic epigenomic changes.