[share_ebook] Microarrays for the Neurosciences: An Essential Guide (Cellular and Molecular Neuroscience)


Author: Daniel H. Geschwind, Jeffrey P. Gregg

Date: 2011-04-16

Pages: 352

Publisher: The MIT Press

Category: Study


Posted on 2011-11-16, by sharebookfree.

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Microarrays for the Neurosciences: An Essential Guide (Cellular and Molecular Neuroscience)


Microarrays for the Neurosciences: An Essential Guide (Cellular and Molecular Neuroscience)
Daniel H. Geschwind, Jeffrey P. Gregg | The MIT Press | 2011-04-16 | 352 pages | English | PDF

The effort to sequence the human genome has generated a new discipline, "functional genomics," or the study of the relationship between the genetic code and its biologic potential. Gene expression studies are made possible not only by the decoding of the human genome, but by the development of new technologies. The preeminent technology in this area, DNA microarrays, is helping to revolutionize the field of neuroscience. Rather than looking at one gene at a time, researchers using DNA microarrays can monitor the expression patterns of large numbers of genes simultaneously. Bridging the traditional gap between molecular neurobiology and systems neurobiology, DNA microarray technology has the potential to elevate molecular genetic studies of the nervous system to the system level.

This book provides a comprehensive guide to the use of DNA microarrays in neuroscience and provides approaches that are applicable to other complex biological systems. Human nervous system tissue is remarkably complex. The number of cell types, the architecture, the developmental program, and the importance of environmental factors in development and functioning all pose particular challenges to the researcher using gene expression studies. After an overview of the technology, the book discusses array scanning and image application, statistical methods for array analysis, specific applications of gene expression studies in the central nervous system, the use of postmortem human tissue, and novel methods for using microarray data to develop hypotheses about regulatory networks.


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