Author

Rizi Ai

University of California San DiegoORCID 0000-0002-1605-7533Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:differential expression· 2 Assay:DNA methylation· 2 Organism:human· 2 Research Focus:database / resource· 1 Approach:experimental assay· 1

Frequent Co-Authors

Mengchi WangiD· 2 shared Shicai FaniD· 2 shared Adrian CamarenaiD· 1 shared Andre Wilberg· 1 shared Bo DingiD· 1 shared Chengyu LiuiD· 1 shared Chris P. Walker· 1 shared Hannah R. DueckiD· 1 shared

Activity by Year

2016-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersBioinformatics

Mengchi WangORCID

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3 papers

Recent·Most cited

BioinformaticsNucleic Acids ResearchPeer-reviewedJun 20, 2019

Identification of DNA motifs that regulate DNA methylation

Mengchi Wang, Kai Zhang, Vu Ngo…·Wei Wang

The paper identifies DNA motifs associated with methylation and unmethylation and shows their functional relevance in DNA methylation regulation and cancer.

55 citations

humanDNA methylation

𝕏 PostBluesky

Bioinformaticsnpj Genomic MedicinePeer-reviewedFeb 1, 2019

Integrative analysis with expanded DNA methylation data reveals common key regulators and pathways in cancers

Shicai Fan, Jianxiong Tang, Nan Li…·Wei Ting Wang

The paper expands DNA methylation data from TCGA using EAGLING, identifies triple-evidenced genes across 13 cancers, and reveals enriched pathways with potential therapeutic value.

48 citations

humanDNA methylation

𝕏 PostBluesky

GenomicsbioRxivPreprintMar 24, 2016

Assessing the measurement transfer function of single-cell RNA sequencing

Hannah R. Dueck, Rizi Ai, Adrian Camarena…·Junhyoung Kim

This study evaluates the performance of three scRNA-seq methods through controlled experiments, finding they reliably detect genes above 5-10 molecules with linear measurement transfer functions.

DOI 10.1101/045450

scRNA-seqstatistical model

𝕏 PostBluesky