Deep learning enables genetic analysis of the human thoracic aorta
Deep learning enables genetic analysis of the human thoracic aorta
About this item
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Author / Creator
Pirruccello, James , Chaffin, Mark D , Stephen Jordan Fleming , Arduini, Alessandro , Lin, Honghuang , Khurshid, Shaan , Chou, Elizabeth L , Friedman, Samuel N , Bick, Alexander G , Lu-Chen, Weng , Choi, Seung Hoan , Amer-Denis Akkad , Batra, Puneet , Tucker, Nathan R , Hall, Amelia W , Roselli, Carolina , Benjamin, Emelia J , Vellarikkal, Shamsudheen K , Gupta, Rajat M , Stegman, Christian M , Ho, Jennifer E , Hoffmann, Udo , Lubitz, Steven A , Philippakis, Anthony , Lindsay, Mark E and Ellinor, Patrick T
Publisher
Cold Spring Harbor: Cold Spring Harbor Laboratory Press
Journal title
Language
English
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Publication information
Publisher
Cold Spring Harbor: Cold Spring Harbor Laboratory Press
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More information
Scope and Contents
Contents
The aorta is the largest blood vessel in the body, and enlargement or aneurysm of the aorta can predispose to dissection, an important cause of sudden death. While rare syndromes have been identified that predispose to aortic aneurysm, the common genetic basis for the size of the aorta remains largely unknown. By leveraging a deep learning architec...
Alternative Titles
Full title
Deep learning enables genetic analysis of the human thoracic aorta
Authors, Artists and Contributors
Author / Creator
Chaffin, Mark D
Stephen Jordan Fleming
Arduini, Alessandro
Lin, Honghuang
Khurshid, Shaan
Chou, Elizabeth L
Friedman, Samuel N
Bick, Alexander G
Lu-Chen, Weng
Choi, Seung Hoan
Amer-Denis Akkad
Batra, Puneet
Tucker, Nathan R
Hall, Amelia W
Roselli, Carolina
Benjamin, Emelia J
Vellarikkal, Shamsudheen K
Gupta, Rajat M
Stegman, Christian M
Ho, Jennifer E
Hoffmann, Udo
Lubitz, Steven A
Philippakis, Anthony
Lindsay, Mark E
Ellinor, Patrick T
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Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2402635723
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2402635723
Other Identifiers
E-ISSN
2692-8205
DOI
10.1101/2020.05.12.091934
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https://www.proquest.com/docview/2402635723?pq-origsite=primo&accountid=13902