Predictive models in gene regulation

Das, D., Zhang, M. Q. (2007) Predictive models in gene regulation. Methods Mol Biol, 377. pp. 95-110. ISSN 978-1-59745-390-5

DOI: 10.1007/978-1-59745-390-5_5

Abstract

Eukaryotic transcription is a complex process. A myriad of biochemical signals cause activators and repressors to bind specific cis-elements on the promoter DNA, which help to recruit the basal transcription machinery that ultimately initiates transcription. In this chapter, we discuss how regression techniques can be effectively used to infer the functional cis-regulatory elements and their cooperativity from microarray data. Examples from yeast cell cycle are drawn to demonstrate the power of these techniques. Periodic regulation of the cell cycle, connection with underlying energetics, and the inference of combinatorial logic are also discussed. An implementation based on regression splines is discussed in detail.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > annotation > gene expression profiling annotation
bioinformatics > quantitative biology
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > gene regulation
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > gene regulation
CSHL Authors:
Communities: CSHL labs > Zhang lab
Depositing User: CSHL Librarian
Date: 2007
Date Deposited: 30 Nov 2011 19:49
Last Modified: 22 Mar 2018 16:22
Related URLs:
URI: http://repository.cshl.edu/id/eprint/22990

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