SVision: a deep learning approach to resolve complex structural variants
Nature Methods, vol. 19, pp. 1230–1233
Authors 11
-
Jiadong Lin Aachen Leiden Institute of Advanced Computer Science Faculty of Science, Leiden University
Leiden University · First Affiliated Hospital of Xi'an Jiaotong University · Xi'an Jiaotong University
Affiliation as printed
Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
Leiden Institute of Advanced Computer Science, Faculty of Science, Leiden University, Leiden, the Netherlands
MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
-
First Affiliated Hospital of Xi'an Jiaotong University · Xi'an Jiaotong University
Affiliation as printed
Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
-
The Jackson Laboratory for Genomic Medicine
Affiliation as printed
The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
-
Macau University of Science and Technology · Xi'an Jiaotong University
Affiliation as printed
MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
Macau Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau
School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, China
-
The Jackson Laboratory for Genomic Medicine
Affiliation as printed
The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
-
Walter A. Kosters Aachen Leiden Institute of Advanced Computer Science Faculty of Science, Leiden University
Affiliation as printed
Leiden Institute of Advanced Computer Science, Faculty of Science, Leiden University, Leiden, the Netherlands
-
Affiliation as printed
MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
School of Computer Science and Technology, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
-
First Affiliated Hospital of Xi'an Jiaotong University · Xi'an Jiaotong University
Affiliation as printed
Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China
-
Heinrich Heine University Düsseldorf
Affiliation as printed
Heinrich Heine University, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Dusseldorf, Germany
-
The Jackson Laboratory for Genomic Medicine · UConn Health
Affiliation as printed
Department of Genetics and Genome Sciences, Institute for Systems Genomics, University of Connecticut Health Center, Farmington, CT, USA
The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
-
Leiden University · First Affiliated Hospital of Xi'an Jiaotong University · Xi'an Jiaotong University
Affiliation as printed
Faculty of Science, Leiden University, Leident, the Netherlands. kaiye@xjtu.edu.cn
Genome Institute, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China. kaiye@xjtu.edu.cn
MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China. kaiye@xjtu.edu.cn
School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China. kaiye@xjtu.edu.cn
The School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China. kaiye@xjtu.edu.cn
Faculty of Science, Leiden University, Leident, the Netherlands
The School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
Cited by 94 stored of 119
Cited by patents worldwide 1 (Lens.org)
-
MACHINE LEARNING METHODS AND SYSTEMS FOR DETECTING STRUCTURAL VARIANTSWO2026080196A1 2026-04-16 Pending