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A Web-Based Workflow for Selecting Gene- and Tissue-Specific Enhancers
Published on: July 18, 2025
Computational identification of active enhancers in model organisms
Chengqi Wang1, Michael Q Zhang, Zhihua Zhang
1CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
Genomics, Proteomics & Bioinformatics
|May 21, 2013
Summary
Enhancers are genomic regions that boost gene transcription. This review surveys computational methods for predicting enhancer activity, crucial for understanding gene regulation across cell types and developmental stages.
Area of Science:
- Genomics
- Molecular Biology
- Computational Biology
Background:
- Enhancers are cis-regulatory elements that increase gene transcription.
- They exhibit cell-type and developmental stage-specific regulation.
- The precise design principles and regulatory network rewiring by enhancers remain unclear.
Purpose of the Study:
- To review current computational approaches for predicting active enhancers.
- To highlight the importance of predicting cell-type specific enhancer activity.
- To discuss future directions in computational enhancer prediction.
Main Methods:
- Survey of existing computational methods for enhancer identification.
- Analysis of techniques for predicting cell-type specific enhancer activity.
- Review of genome-wide enhancer identification technologies.
Main Results:
- Computational methods are central to understanding enhancer function.
- Predicting cell-type specific enhancer activity is a key challenge.
- Current methods provide a foundation for future research.
Conclusions:
- Further development of predictive computational methods is essential.
- Understanding enhancer mechanisms will advance gene regulation knowledge.
- This review provides a roadmap for future computational studies on enhancers.
