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Imaging genetics
~
Batmanghelich, Nematollah K.
Imaging genetics
Record Type:
Electronic resources : Monograph/item
Title/Author:
Imaging geneticsedited by Adrian V. Dalca, Nematollah K. Batmanghelich, Li Shen, Mert R. Sabuncu.
other author:
Dalca, Adrian V.
Published:
London, United Kingdom :Academic Press is an imprint of Elsevier,2018.
Description:
1 online resource.
Subject:
Genetics.
Online resource:
https://www.sciencedirect.com/science/book/9780128139684
ISBN:
9780128139691 (electronic bk.)
Imaging genetics
Imaging genetics
[electronic resource] /edited by Adrian V. Dalca, Nematollah K. Batmanghelich, Li Shen, Mert R. Sabuncu. - London, United Kingdom :Academic Press is an imprint of Elsevier,2018. - 1 online resource. - The elsevier and MICCAI Society book series. - Elsevier and MICCAI Society book series..
Includes bibliographical references and index.
Multisite metaanalysis of image-wide genome-wide associations with morphometry -- Genetic connectivity : correlated genetic control of cortical thickness, brain volume, and white matter -- Integration of network-based biological knowledge with white matter features in preterm infants using the graph-guided group lasso -- Classifying schizophrenia subjects by fusing networks from single-nucleotide polymorphisms, DNA methylation, and functional magnetic resonance imaging data -- Genetic correlation between cortical gray matter thickness and white matter connections -- Bootstrapped sparse canonical correlation analysis: mining stable imaging and genetic associations with implicit structure learning -- A network-based framework for mining high-level imaging genetic associations -- Bayesian feature selection for ultra-high dimensional imaging genetics data -- Continuous inflation analysis: a threshold-free method to estimate genetic overlap and boost power in imaging genetics.
"Imaging Genetics presents the latest research in imaging genetics methodology for discovering new associations between imaging and genetic variables, providing an overview of the state-of the-art in the field. Edited and written by leading researchers, this book is a beneficial reference for students and researchers, both new and experienced, in this growing area. The field of imaging genetics studies the relationships between DNA variation and measurements derived from anatomical or functional imaging data, often in the context of a disorder. While traditional genetic analyses rely on classical phenotypes like clinical symptoms, imaging genetics can offer richer insights into underlying, complex biological mechanisms. Contains an introduction describing how the field has evolved to the present, together with perspectives on its future direction and challenges Describes novel application domains and analytic methods that represent the state-of-the-art in the burgeoning field of imaging geneticsIntroduces a novel, large-scale analytic framework that involves multi-site, image-wide, genome-wide associations"--
ISBN: 9780128139691 (electronic bk.)Subjects--Topical Terms:
189015
Genetics.
Index Terms--Genre/Form:
214472
Electronic books.
LC Class. No.: QH430
Dewey Class. No.: 576.5
National Library of Medicine Call No.: 2018 A-872
Imaging genetics
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Imaging genetics
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[electronic resource] /
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edited by Adrian V. Dalca, Nematollah K. Batmanghelich, Li Shen, Mert R. Sabuncu.
260
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London, United Kingdom :
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Academic Press is an imprint of Elsevier,
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2018.
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1 online resource.
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The elsevier and MICCAI Society book series
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Includes bibliographical references and index.
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Multisite metaanalysis of image-wide genome-wide associations with morphometry -- Genetic connectivity : correlated genetic control of cortical thickness, brain volume, and white matter -- Integration of network-based biological knowledge with white matter features in preterm infants using the graph-guided group lasso -- Classifying schizophrenia subjects by fusing networks from single-nucleotide polymorphisms, DNA methylation, and functional magnetic resonance imaging data -- Genetic correlation between cortical gray matter thickness and white matter connections -- Bootstrapped sparse canonical correlation analysis: mining stable imaging and genetic associations with implicit structure learning -- A network-based framework for mining high-level imaging genetic associations -- Bayesian feature selection for ultra-high dimensional imaging genetics data -- Continuous inflation analysis: a threshold-free method to estimate genetic overlap and boost power in imaging genetics.
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"Imaging Genetics presents the latest research in imaging genetics methodology for discovering new associations between imaging and genetic variables, providing an overview of the state-of the-art in the field. Edited and written by leading researchers, this book is a beneficial reference for students and researchers, both new and experienced, in this growing area. The field of imaging genetics studies the relationships between DNA variation and measurements derived from anatomical or functional imaging data, often in the context of a disorder. While traditional genetic analyses rely on classical phenotypes like clinical symptoms, imaging genetics can offer richer insights into underlying, complex biological mechanisms. Contains an introduction describing how the field has evolved to the present, together with perspectives on its future direction and challenges Describes novel application domains and analytic methods that represent the state-of-the-art in the burgeoning field of imaging geneticsIntroduces a novel, large-scale analytic framework that involves multi-site, image-wide, genome-wide associations"--
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Provided by publisher.
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Online resource; title from PDF title page (EBSCO, viewed October 12, 2017).
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Genetics.
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189015
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Imaging systems in biology.
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Human genetics
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Genetic Variation
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Genetic Association Studies.
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Dalca, Adrian V.
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Batmanghelich, Nematollah K.
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(Nematollah Kayhan),
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Sabuncu, Mert Rory,
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Shen, Li
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https://www.sciencedirect.com/science/book/9780128139684
based on 0 review(s)
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電子館藏
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000000187061
電子館藏
1圖書
電子書
EB QH430 2018
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
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https://www.sciencedirect.com/science/book/9780128139684
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