Author

Michael Perlmutter

Boise State UniversityORCID 0000-0001-9829-4016Unclaimed 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:differential expression· 2 Research Focus:gene regulatory network inference· 2 Approach:graph neural network· 2 Assay:scRNA-seq· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Approach:deep learning· 1 Research Focus:spatial domain detection· 1

Frequent Co-Authors

Smita KrishnaswamyiD· 2 shared Aarthi VenkatiD· 1 shared Eric FagerbergiD· 1 shared Holly R. SteachiD· 1 shared John AttanasioiD· 1 shared Matthew HirniD· 1 shared Natalia B. IvanovaiD· 1 shared Nikhil S. JoshiiD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersBioinformatics

Smita KrishnaswamyORCID

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2 papers

Recent·Most cited

BioinformaticsNature Computational SciencePeer-reviewedDec 20, 2024

Mapping the gene space at single-cell resolution with gene signal pattern analysis

Aarthi Venkat, Sam Leone, Scott E. Youlten…·Smita Krishnaswamy

This paper introduces GSPA, a method to map gene space at single-cell resolution, enabling gene characterization and analysis of gene expression patterns across biological tasks.

3 citations

scRNA-seqgraph neural network

𝕏 PostBluesky

BioinformaticsLecture notes in computer sciencePeer-reviewedJan 1, 2024

Inferring Metabolic States from Single Cell Transcriptomic Data via Geometric Deep Learning

Holly R. Steach, Siddharth Viswanath, Yixuan He…·Smita Krishnaswamy

This paper introduces GEFMAP, a geometric deep learning method to predict metabolic flux from scRNA-seq data, estimating reaction rates in metabolic networks.

7 citationstop 2%

scRNA-seqdeep learning

𝕏 PostBluesky