Author

J. H. Macke

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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Biophysics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:benchmarking· 1 Organism:Drosophila· 1 Assay:imaging· 1 Assay:spatial transcriptomics· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

S. C. Turaga· 2 shared A. Kreshuk· 1 shared A. Nern· 1 shared A. Speiser· 1 shared C. J. Obara· 1 shared E. Gruntman· 1 shared F. D. Tschopp· 1 shared J. K. Lappalainen· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersNeuroscience

S. C. Turaga

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Author profile →

2 papers

Recent·Most cited

Connectome-constrained deep mechanistic networks predict neural responses across the fly visual system at single-neuron resolution

J. K. Lappalainen, F. D. Tschopp, S. Prakhya, M. McGill, A. Nern, K. Shinomiya, S.-y. Takemura, E. Gruntman, J. H. Macke, S. C. Turaga

The paper predicts neural responses in the fly visual system using a connectome-constrained deep mechanistic model, showing agreement with experimental data across 24 studies.

bioRxiv · Mar 11, 2023 · PreprintNeuroscience

Deep learning enables fast and dense single-molecule localization with high accuracy

A. Speiser, L.-R. Müller, U. Matti, C. J. Obara, W. R. Legant, A. Kreshuk, J. H. Macke, J. Ries, S. C. Turaga

This paper introduces DECODE, a deep learning tool that improves single-molecule localization speed and density in SMLM with high accuracy across various imaging conditions.

bioRxiv · Oct 26, 2020Biophysics