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Ying Ji
Ying Ji
vanderbilt.eduÀÇ À̸ÞÀÏ È®ÀÎµÊ - ȨÆäÀÌÁö
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A Bayesian framework that integrates multi-omics data and gene networks predicts risk genes from schizophrenia GWAS data
Q Wang, R Chen, F Cheng, Q Wei, Y Ji, H Yang, X Zhong, R Tao, Z Wen, ...
Nature neuroscience 22 (5), 691-699, 2019
1302019
Anti-apoptotic mutations desensitize human pluripotent stem cells to mitotic stress and enable aneuploid cell survival
J Zhang, AJ Hirst, F Duan, H Qiu, R Huang, Y Ji, L Bai, F Zhang, ...
Stem cell reports 12 (3), 557-571, 2019
412019
De novo pattern discovery enables robust assessment of functional consequences of non-coding variants
H Yang, R Chen, Q Wang, Q Wei, Y Ji, G Zheng, X Zhong, NJ Cox, B Li
Bioinformatics 35 (9), 1453-1460, 2019
182019
Incorporating European GWAS findings improve polygenic risk prediction accuracy of breast cancer among East Asians
Y Ji, J Long, SS Kweon, D Kang, M Kubo, B Park, XO Shu, W Zheng, ...
Genetic Epidemiology 45 (5), 471-484, 2021
92021
TVAR: assessing tissue-specific functional effects of non-coding variants with deep learning
H Yang, R Chen, Q Wang, Q Wei, Y Ji, X Zhong, B Li
Bioinformatics 38 (20), 4697-4704, 2022
32022
Integration of multidimensional splicing data and GWAS summary statistics for risk gene discovery
Y Ji, Q Wei, R Chen, Q Wang, R Tao, B Li
PLoS genetics 18 (6), e1009814, 2022
12022
A Bayesian framework to integrate multi-level genome-scale data for Autism risk gene prioritization
Y Ji, R Chen, Q Wang, Q Wei, R Tao, B Li
BMC bioinformatics 23 (1), 1-17, 2022
2022
Leveraging Gene-Level Prediction as Informative Covariate in Hypothesis Weighting Improves Power for Rare Variant Association Studies
Y Ji, R Chen, Q Wang, Q Wei, R Tao, B Li
Genes 13 (2), 381, 2022
2022
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