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SELEX experiments: New prospects, applications and data analysis in inferring regulatory pathways

Paper ID Volume ID Publish Year Pages File Format Full-Text
14091 1147 2007 11 PDF Available
Title
SELEX experiments: New prospects, applications and data analysis in inferring regulatory pathways
Abstract

Systematic Evolution of Ligands by EXponential enrichment (SELEX) is an experimental procedure that allows extraction, from an initially random pool of oligonucleotides, of the oligomers with a desired binding affinity for a given molecular target. The procedure can be used to infer the strongest binders for a given DNA or RNA binding protein, and the highest affinity binding sequences isolated through SELEX can have numerous research, diagnostic and therapeutic applications. Recently, important new modifications of the SELEX protocol have been proposed. In particular, a modification of the standard SELEX procedure allows generating a dataset from which protein–DNA interaction parameters can be determined with unprecedented accuracy. Another variant of SELEX allows investigating interactions of a protein with nucleic-acid fragments derived from the entire genome of an organism. We review here different SELEX-based methods, with particular emphasis on the experimental design and on the applications aimed at inferring protein–DNA interactions. In addition to the experimental issues, we also review relevant methods of data analysis, as well as theoretical modeling of SELEX.

Keywords
In vitro selection; High-throughput SELEX; SELEX-SAGE; Genomic SELEX; SELEX modeling; Protein–nucleic acid interactions
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SELEX experiments: New prospects, applications and data analysis in inferring regulatory pathways
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biomolecular Engineering - Volume 24, Issue 2, June 2007, Pages 179–189
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us