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Deep learning enables accurate detection and characterization of complex image-based structures
With the support of the National Natural Science Foundation of China (approval number: 32125009, 32070663), Professor Ye Kai's team from the School of Automation of the Faculty of Telecommunications of Xi'an Jiaotong University and the First Affiliated Hospital have made progress
in the identification method of complex structural variation of the genome 。 The research results were published in the journal Nature Methods on September 16, 2022, titled "SVision: A deep learning approach to resolve complex structural variants
.
Due to the high degree of sequence repeatability and the existence of a large number of unknown complex types in the regions with high incidence of genomic structural variation, there are a large number of misdetection and omission detection in the computational methods based on modeling strategies in traditional genomic analysis, and it is difficult to deeply explore the role
of structural variation in the evolution of biological traits and disease generation.
This work discovers the complex structural variation of the genome from scratch through deep learning strategies, and provides new ideas
for the calculation theory of biological big data based on cutting-edge information technology.
