Author

Weixuan Fu

University of PennsylvaniaORCID 0000-0002-6434-5468Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 3 Research Focus:differential expression· 3 Approach:machine learning (classical)· 3 Assay:bulk RNA-seq· 2 Research Focus:gene regulatory network inference· 2 Organism:human· 2 Research Focus:cell type annotation· 1 Assay:GWAS summary statistics· 1

Frequent Co-Authors

Jason H. MooreiD· 3 shared Elisabetta ManduchiiD· 2 shared Trang T. LeiD· 2 shared Joseph D. RomanoiD· 1 shared Stefano RubertoiD· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 8 mutual co-author links

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3 shared papersBioinformatics

Jason H. MooreORCID

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3 papers

Recent·Most cited

BioinformaticsIEEE Transactions on Computational Biology and BioinformaticsPeer-reviewedJul 26, 2021

Genetic analysis of coronary artery disease using tree-based automated machine learning informed by biology-based feature selection

Elisabetta Manduchi, Trang T. Le, Weixuan Fu, Jason H. Moore

This study uses TPOT to identify SNPs associated with coronary artery disease, finding 28 recurrent SNPs with functional relevance to known CAD genes and distinct clusters of predicted CAD cases.

22 citations

humanGWAS summary statistics

𝕏 PostBluesky

BioinformaticsBMC BioinformaticsPeer-reviewedOct 1, 2020

Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses

Elisabetta Manduchi, Weixuan Fu, Joseph D. Romano…·Jason H. Moore

The paper extends the TPOT AutoML tool to include covariate adjustments in biomedical data analysis, showing its utility in toxicogenomics and gene expression studies.

23 citations

bulk RNA-seqmachine learning (classical)

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GenomicsBioinformaticsPeer-reviewedJun 2, 2019

Scaling tree-based automated machine learning to biomedical big data with a dataset selector

Trang T. Le, Weixuan Fu, Jason H. Moore

The paper introduces two features to TPOT, a machine learning tool, to improve its scalability and efficiency for biomedical big data analysis.

458 citationstop 1%

humanbulk RNA-seq

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