Quantitative Visualization of ChIP-chip Data by Using Linked Views

PDF Version Also Available for Download.

Description

Most analyses of ChIP-chip in vivo DNA binding have focused on qualitative descriptions of whether genomic regions are bound or not. There is increasing evidence, however, that factors bind in a highly overlapping manner to the same genomic regions and that it is quantitative differences in occupancy on these commonly bound regions that are the critical determinants of the different biological specificity of factors. As a result, it is critical to have a tool to facilitate the quantitative visualization of differences between transcription factors and the genomic regions they bind to understand each factor's unique roles in the network. We ... continued below

Creation Information

Huang, Min-Yu; Weber, Gunther; Li, Xiao-Yong; Biggin, Mark & Hamann, Bernd November 5, 2010.

Context

This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 15 times . More information about this article can be viewed below.

Who

People and organizations associated with either the creation of this article or its content.

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this article. Follow the links below to find similar items on the Digital Library.

Description

Most analyses of ChIP-chip in vivo DNA binding have focused on qualitative descriptions of whether genomic regions are bound or not. There is increasing evidence, however, that factors bind in a highly overlapping manner to the same genomic regions and that it is quantitative differences in occupancy on these commonly bound regions that are the critical determinants of the different biological specificity of factors. As a result, it is critical to have a tool to facilitate the quantitative visualization of differences between transcription factors and the genomic regions they bind to understand each factor's unique roles in the network. We have developed a framework which combines several visualizations via brushing-and-linking to allow the user to interactively analyze and explore in vivo DNA binding data of multiple transcription factors. We describe these visualization types and also provide a discussion of biological examples in this paper.

Subjects

Source

  • Workshop on Integrative Data Analysis in Systems Biology (IDASB10)

Language

Item Type

Identifier

Unique identifying numbers for this article in the Digital Library or other systems.

  • Report No.: LBNL-4491E
  • Grant Number: DE-AC02-05CH11231
  • Office of Scientific & Technical Information Report Number: 1012475
  • Archival Resource Key: ark:/67531/metadc833762

Collections

This article is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

What responsibilities do I have when using this article?

When

Dates and time periods associated with this article.

Creation Date

  • November 5, 2010

Added to The UNT Digital Library

  • May 19, 2016, 3:16 p.m.

Description Last Updated

  • Nov. 8, 2016, 12:09 p.m.

Usage Statistics

When was this article last used?

Yesterday: 0
Past 30 days: 1
Total Uses: 15

Interact With This Article

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

International Image Interoperability Framework

IIF Logo

We support the IIIF Presentation API

Huang, Min-Yu; Weber, Gunther; Li, Xiao-Yong; Biggin, Mark & Hamann, Bernd. Quantitative Visualization of ChIP-chip Data by Using Linked Views, article, November 5, 2010; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc833762/: accessed November 16, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.