Author

Stefan Pietrzak

University of Wisconsin–Madison

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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Bioinformatics· 1 Developmental Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 2 Assay:scRNA-seq· 2 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1 Assay:scATAC-seq· 1

Frequent Co-Authors

Alireza Fotuhi SiahpiraniiD· 2 shared Rupa SridharaniD· 2 shared Sunnie Grace McCallaiD· 2 shared Sushmita RoyiD· 2 shared Amber S. ZhouiD· 1 shared Gopal IyeriD· 1 shared Khoa A. TraniD· 1 shared Nur Zafirah Zaidan· 1 shared

Activity by Year

2019-2022 · peak 1/yr

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10 top collaborators · 37 mutual co-author links

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2 shared papersBioinformatics

Alireza Fotuhi SiahpiraniORCID

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2 papers

Recent·Most cited

Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets

Shilu Zhang, Saptarshi Pyne, Stefan Pietrzak, Spencer Halberg, Sunnie Grace McCalla, Alireza Fotuhi Siahpirani, Rupa Sridharan, Sushmita Roy

This paper introduces scMTNI, a framework to infer cell type-specific gene regulatory networks on cell lineages using scRNA-seq and scATAC-seq data, showing its effectiveness on simulated and real datasets.

bioRxiv · Jul 25, 2022 · PreprintBioinformatics

Defining reprogramming checkpoints from single-cell analysis of induced pluripotency

Khoa A. Tran, Stefan Pietrzak, Nur Zafirah Zaidan, Alireza Fotuhi Siahpirani, Sunnie Grace McCalla, Amber S. Zhou, Gopal Iyer, Sushmita Roy, Rupa Sridharan

This study identifies reprogramming checkpoints in iPSC generation by analyzing single-cell transcriptomes and reveals key gene interactions and regulatory mechanisms.

Cell Reports · May 1, 2019Peer-reviewedDevelopmental Biology