Author

Scott X. Atwell

Helmholtz MunichORCID 0000-0001-9943-3524Unclaimed ORCID profile · follow to get notified of new preprints

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Scott X. Atwell1 paper

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Assay:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:dimensionality reduction· 1 Research Focus:software / tool· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

Carsten MarriD· 2 shared Dominik WaibeliD· 2 shared Matthias MeieriD· 2 shared Ario SadafiiD· 1 shared Niklas KiermeyeriD· 1 shared Sandra WiedenmanniD· 1 shared Sayedali Shetab BoushehriiD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 17 mutual co-author links

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2 shared papersBioinformatics

Carsten MarrORCID

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2 papers

Recent·Most cited

BioinformaticsCell Reports MethodsPeer-reviewedJul 1, 2023

Label-free imaging of 3D pluripotent stem cell differentiation dynamics on chip

Scott X. Atwell, Dominik Waibel, Sayedali Shetab Boushehri…·Matthias Meier

The paper introduces a label-free deep learning method to predict nuclear staining in 3D stem cell cultures from bright-field images, enabling high-resolution tracking of differentiation dynamics.

13 citations

𝕏 PostBluesky

BioinformaticsiSciencePeer-reviewedJan 1, 2022

SHAPR predicts 3D cell shapes from 2D microscopic images

Dominik Waibel, Niklas Kiermeyer, Scott X. Atwell…·Carsten Marr

SHAPR predicts 3D cell shapes from 2D images, improving accuracy over existing methods and enabling morphometric analysis of cell aggregates.

15 citations

𝕏 PostBluesky