Author

Jaeho Oh

Korea Advanced Institute of Science and TechnologyORCID 0000-0002-1522-0167Unclaimed ORCID profile · follow to get notified of new preprints

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Jaeho Oh1 paper

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Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:GWAS summary statistics· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Hyo‐Jeong BaniD· 1 shared Jeong Yeon KimiD· 1 shared Jung Kyoon ChoiiD· 1 shared Min Kyung SungiD· 1 shared Seongwon HwangiD· 1 shared Seulkee LeeiD· 1 shared Taeyeop LeeiD· 1 shared Woojin YangiD· 1 shared

Activity by Year

2019-2019 · peak 1/yr

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8 top collaborators · 28 mutual co-author links

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1 shared paperGenetics

Hyo‐Jeong BanORCID

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1 paper

Recent·Most cited

Convolutional neural network model to predict causal risk factors that share complex regulatory features

Taeyeop Lee, Min Kyung Sung, Seulkee Lee, Woojin Yang, Jaeho Oh, Jeong Yeon Kim, Seongwon Hwang, Hyo‐Jeong Ban, Jung Kyoon Choi

The paper develops a convolutional neural network to predict causal noncoding variants with regulatory function in GWAS data, identifying variants in active regulatory regions and associated genes for psychiatric and autoimmune diseases.

Nucleic Acids Research · Oct 1, 2019Peer-reviewedGenetics