Author

Hu Huang

University of MinnesotaORCID 0000-0002-4384-3804Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:variant effect prediction· 1 Assay:whole-exome sequencing· 1

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Caleb J. Kennedy· 1 shared Cynthia Vierra‐Green· 1 shared Stephen Spellman· 1 shared

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2019-2019 · peak 1/yr

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3 top collaborators · 3 mutual co-author links

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1 shared paperBioinformatics

Caleb J. Kennedy

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1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintApr 18, 2019

Iterative feature selection method to discover predictive variables and interactions for high-dimensional transplant genomic data

Hu Huang, Cynthia Vierra‐Green, Stephen Spellman, Caleb J. Kennedy

The paper introduces an iterative feature selection method to identify predictive SNPs and their interactions in high-dimensional transplant genomic data, showing it can reduce SNP sets to less than 0.05%.

DOI 10.1101/605428

humanwhole-exome sequencing

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