You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.
You must be logged in to perform this action.

End Sequence Profiling Computational Lab - Oliver Hampton

No Strings Attached
Author:
Subject:
Science and Technology
Institution Name:
SciVee
Collection:
SciVee
Grade Level:
Post-secondary
Abstract:

Computational laboratory: Starting from a set of breast cancer BACs (bacterial artificial chromosomes) End Sequence Profiling (ESP) is performed. ESP analysis sequences the ends of insert DNA in order to characterize genomic rearrangements that may be involved in breast cancer progression. In this study, genomic rearrangements are characterized from 100 breast cancer BACs and 10,000 Fosmids (derived from a pool of the 100 originating BAC) using ESP. Analysis and comparison of both BAC and Fosmid based data sets will be performed. Part of the Computer-Aided Discovery Methods course taught at Baylor College of Medicine.

Languages:
English
Media Format:
Video
Conditions of Use:
Creative Commons Attribution 3.0
Creative Commons Attribution 3.0

Comments

Send link to this page

The e-mail address to send this link to.
A comment about this link.
Log in or Register

Rate and Review

Evaluate Resource What is this?

Common Core Standards

Align Resource
Not Yet Aligned

    Add new alignment tag:

    Share

    Tags

    Keywords, descriptive words, interested groups & more