Author

Natalia B. Ivanova

University of GeorgiaORCID 0000-0002-6494-6247Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:scRNA-seq· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Research Focus:gene regulatory network inference· 1 Approach:graph neural network· 1 Organism:human· 1

Frequent Co-Authors

Matthew HirniD· 2 shared Smita KrishnaswamyiD· 2 shared Antonia M. G. van den ElzeniD· 1 shared Daniel B. BurkhardtiD· 1 shared David van DijkiD· 1 shared Guy WolfiD· 1 shared Holly R. SteachiD· 1 shared Kevin R. MooniD· 1 shared

Activity by Year

2019-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersBioinformatics

Matthew HirnORCID

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2 papers

Recent·Most cited

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

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BioinformaticsNature BiotechnologyPeer-reviewedDec 1, 2019

Visualizing Structure and Transitions for Biological Data Exploration

Kevin R. Moon, David van Dijk, Zheng Wang…·Smita Krishnaswamy

The paper introduces PHATE, a visualization method that captures nonlinear structure in biological data, showing it preserves patterns better than existing tools and reveals novel insights in scRNA-seq data.

1,064 citationstop 1%

humanscRNA-seq

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