Author

Xiao Dang

BGI Group (China)ORCID 0000-0001-6609-2807Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Research Focus:differential expression· 1 Organism:human· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Hankui LiuiD· 2 shared Jianguo ZhangiD· 2 shared Chang-Geng Tian· 1 shared Chen YeiD· 1 shared Dongzhu LeiiD· 1 shared Fang CheniD· 1 shared Hao-Xiang Sun· 1 shared Huanming YangiD· 1 shared

Activity by Year

2019-2020 · peak 1/yr

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10 top collaborators · 38 mutual co-author links

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2 shared papersBioinformatics

Hankui LiuORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintApr 13, 2020

A phenotype-specific framework for identifying the eye abnormalities causative nonsynonymous-variants

Hankui Liu, Xiao Dang, Li-Ping Guan…·Jianguo Zhang

This paper introduces a phenotype-specific framework to identify causative nonsynonymous variants in eye abnormalities, achieving high accuracy and precision in pathogenicity prediction.

2 citations

humanwhole-genome sequencing

𝕏 PostBluesky

GeneticsHuman GeneticsPeer-reviewedMay 8, 2019

Gene pathogenicity prediction of Mendelian diseases via the Random Forest algorithm

Sijie He, Weiwei Chen, Hankui Liu…·Jianguo Zhang

This study uses a random forest algorithm to predict gene pathogenicity for Mendelian diseases, achieving 80% accuracy and identifying 10,399 protein-coding genes as potential Mendelian disease genes.

7 citations

machine learning (classical)differential expression

𝕏 PostBluesky