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Imaging genetics

Dalca, Adrian V.

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Imaging genetics

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Imaging genetics/ edited by Adrian V. Dalca, Nematollah K. Batmanghelich, Li Shen, Mert R. Sabuncu.
其他作者:	Dalca, Adrian V.
出版者:	London, United Kingdom :Academic Press is an imprint of Elsevier, : 2018.,
面頁冊數:	1 online resource.
內容註:	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.
標題:	Genetics. -
電子資源:	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:

530508
Genetics.
Index Terms--Genre/Form:

542853
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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260 $a London, United Kingdom : $b Academic Press is an imprint of Elsevier, $c 2018.
300 $a 1 online resource.
490 1 $a The elsevier and MICCAI Society book series
504 $a Includes bibliographical references and index.
505 0 $a 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.
520 $a "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"-- $c Provided by publisher.
588 0 $a Online resource; title from PDF title page (EBSCO, viewed October 12, 2017).
650 0 $a Genetics. $3 530508
650 0 $a Imaging systems in biology. $3 629357
650 0 $a Human genetics $x Variation. $3 560726
650 0 $a Imaging systems in genetics. $3 3462828
650 1 2 $a Genetic Variation $x genetics. $3 3462829
650 2 2 $a Genetic Association Studies. $3 3462830
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700 1 $a Dalca, Adrian V. $q (Adrian Vasile), $e editor. $3 3462824
700 1 $a Batmanghelich, Nematollah K. $q (Nematollah Kayhan), $e editor. $3 3462825
700 1 $a Sabuncu, Mert Rory, $d 1979- $e editor. $3 3462826
700 1 $a Shen, Li $c (Radiologist), $e editor. $3 3462827
830 0 $a Elsevier and MICCAI Society book series. $3 3235387
856 4 0 $u https://www.sciencedirect.com/science/book/9780128139684