Author

Xinqiong Yang

Stanford Medicine

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genomics· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Assay:ChIP-seq· 2 Approach:machine learning (classical)· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Organism:mouse· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Michael P. SnyderiD· 3 shared Minyi ShiiD· 3 shared Annika K K WeimeriD· 2 shared Anshul Bharat KundajeiD· 2 shared Jessika AdrianiD· 2 shared Lixia JiangiD· 2 shared Alex Hawkins‐HookeriD· 1 shared Ali MortazaviiD· 1 shared

Activity by Year

2023-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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3 shared papersGenomics

Michael P. SnyderORCID

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Author profile →

3 papers

Recent·Most cited

Comparative atlas of genome-wide chromatin-associated protein co-occupancy

Shannon M. White, Belle A. Moyers, Tao Wang, Mark Mackiewicz, Annika K K Weimer, Fabian Grubert, Vivekanandan Ramalingam, Jay X. J. Luo, Lixia Jiang, Minyi Shi, Xinqiong Yang, Tristan Chou, Jie Zhai, Konor von Kraut, Jessika Adrian, , Michael P. Snyder

The paper identifies cell type-specific and shared chromatin-associated protein co-association modules using ChIP-Seq and machine learning in K562 and HepG2 cells.

bioRxiv · Dec 17, 2024 · PreprintGenomics

The ENCODE mouse postnatal developmental time course identifies regulatory programs of cell types and cell states

Elisabeth Rebboah, Narges Rezaie, Brian A. Williams, Annika K K Weimer, Minyi Shi, Xinqiong Yang, Heidi Yahan Liang, Louise A. Dionne, Fairlie Reese, Diane E. Trout, Jennifer Jou, Ingrid Youngworth, Laura G. Reinholdt, Samuel Morabito, Michael P. Snyder, , Ali Mortazavi

The paper identifies regulatory programs in postnatal mouse development using single-nucleus data, revealing cell-type-specific and common regulatory topics across multiple tissues.

bioRxiv · Jun 12, 2024 · PreprintGenomics

The ENCODE Imputation Challenge: A critical assessment of methods for cross-cell type imputation of epigenomic profiles

Jacob Matthew Schreiber, Carles A. Boix, Jin wook Lee, Hongyang Li, Yuanfang Guan, Chun-Chieh Chang, Jen-Chien Chang, Alex Hawkins‐Hooker, Bernhard Schölkopf, Gabriele Schweikert, Mateo Rojas-Carulla, Arif Canakoglu, Francesco Guzzo, Luca Nanni, Marco Masseroli, , ENCODE Imputation Challenge Participants

The paper evaluates 23 imputation models for cross-cell type epigenomic data, finding quality assessment challenging due to distributional shifts, data availability, and redundant metrics.

Genome biology · Apr 18, 2023Peer-reviewedBioinformatics