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Methods in Genomic Neuroscience

List Price: $91.99
SKU:
9780367455132
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  • Product Details

    Author:
    Hemin R. Chin, Steven O. Moldin
    Format:
    Paperback
    Pages:
    360
    Publisher:
    CRC Press (December 18, 2019)
    Language:
    English
    ISBN-13:
    9780367455132
    Weight:
    23.75oz
    Dimensions:
    6.125" x 9.1875"
    File:
    TAYLORFRANCIS-TayFran_260730050354430-20260730.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $91.99
    Case Pack:
    1
    As low as:
    $87.39
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Audience:
    Professional and scholarly
    Country of Origin:
    United States
    Pub Discount:
    30
    Imprint:
    CRC Press
  • Overview

    The past few years have witnessed extraordinary advances in molecular genetic techniques and the accumulation of structural genomics information and resources in both human and model organisms. With the development of new technologies and the availability of resources like the sequence of eukaryotic genomes, problems of a previously unthinkable scope are now being routinely solved in neuroscience and many other areas of biomedical research. The results of these studies, in turn, are having, and will continue to have, profound impact on experimental approaches and designs for manipulating genes, the genome, and model organisms as a means of gaining insights into nervous system functioning and complex behavior.

    Methods in Genomic Neuroscience provides newcomers and experienced researchers with a reference guide for applying powerful, state-of-the-art molecular genetic techniques to the study of neural and behavioral systems. It thereby provides a foundation by which data on gene expression and function may be used to develop new therapeutic strategies for brain diseases.

    Authored by researchers in the forefront of genomic neuroscience, the book addresses state-of-the-art tools and technologies for global analysis of genes influencing the nervous system and its disorders. An emphasis is placed on massively parallel approaches for analyzing the avalanche of data that is being generated from the full genomic sequence of humans and model systems. Specific topics include human sequence variation, methods for discovering disease vulnerability genes, gene-environmental interaction, gene expression analysis using DNA microarrays, random mutagenesis, gene trap approaches for studying brain development, neural stem cells, gene targeting, and gene delivery.