Author

Viswesh Periyasamy

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

Click to filter author papers

Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 2 Assay:scRNA-seq· 2 Approach:benchmark study· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Organism:mouse· 1

Frequent Co-Authors

Alireza Fotuhi SiahpiraniiD· 2 shared Sushmita RoyiD· 2 shared Amr A. AbdeeniD· 1 shared Benjamin SteyeriD· 1 shared Bikash Ranjan PattnaikiD· 1 shared Budd A. TuckeriD· 1 shared Cole Bacig· 1 shared David M. GammiD· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Alireza Fotuhi SiahpiraniORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Identifying strengths and weaknesses of methods for computational network inference from single cell RNA-seq data

Sunnie Grace McCalla, Alireza Fotuhi Siahpirani, Jiaxin Li, Saptarshi Pyne, Matthew Stone, Viswesh Periyasamy, Junha Shin, Sushmita Roy

The paper benchmarks eleven network inference methods on scRNA-seq datasets to evaluate their performance in recovering gene regulatory networks.

G3 Genes Genomes Genetics · Jan 10, 2023Peer-reviewedBioinformatics

Human iPSC modeling reveals mutation-specific responses to gene therapy in Best disease

Divya Sinha, Benjamin Steyer, Pawan Kumar Shahi, Katherine P. Mueller, Rasa Valiauga, Kimberly L. Edwards, Cole Bacig, Stephanie S. Steltzer, Sandhya Srinivasan, Amr A. Abdeen, Evan Cory, Viswesh Periyasamy, Alireza Fotuhi Siahpirani, Edwin M. Stone, Budd A. Tucker, , David M. Gamm

This study uses iPSC-RPE models to evaluate gene augmentation and editing for Best disease, finding that some mutations respond to gene therapy while others require genome editing.

bioRxiv · Jan 31, 2020 · PreprintGenetics