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Related Experiment Video

Updated: May 9, 2026

Mapping Mammalian 3D Genome Interactions with Micro-C-XL

Mapping Mammalian 3D Genome Interactions with Micro-C-XL

Published on: November 3, 2023

MIG: Multi-Image Genome viewer.

Simon J McGowan¹, Jim R Hughes, Zong-Pei Han

¹Computational Biology Research Group and Molecular Haemotology Unit, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Headington, Oxford OX3 9DS, UK.

Bioinformatics (Oxford, England)

|July 12, 2013

Summary

This summary is machine-generated.

The Multi-Image Genome (MIG) viewer is a web tool for analyzing large genomic datasets. It efficiently visualizes, filters, and exports genome browser data for various applications.

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Last Updated: May 9, 2026

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Genome browsers are essential tools for visualizing genomic data.
Analyzing large-scale genomic datasets presents significant computational challenges.
Existing tools may lack the flexibility to handle diverse data types and large volumes.

Purpose of the Study:

To introduce the Multi-Image Genome (MIG) viewer, a novel web-based application.
To provide a scalable solution for visualizing and analyzing numerous genome browser regions.
To facilitate data querying, filtering, and export for downstream genomic research.

Main Methods:

Development of a web-based application for multi-image genome data visualization.
Implementation of functionalities for querying and filtering large sets of genome browser regions.
Integration of data export options in various standard formats.

Main Results:

The MIG viewer enables efficient visualization of thousands of genome browser regions.
The application successfully supports the analysis of ChIP-Seq and RNA-Seq data.
Somatic mutations in genome resequencing projects can be effectively detected using MIG.

Conclusions:

The Multi-Image Genome (MIG) viewer is a versatile tool for genomic data analysis.
Its capabilities extend to various applications, including epigenomics and transcriptomics.
MIG provides a robust platform for exploring and interpreting complex genomic datasets.