Author

S. B. Jensen

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· 3

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Research Focus:benchmarking· 2 Research Focus:cell signaling & trafficking· 1 Organism:human· 1 Assay:imaging· 1 Organism:plant (other)· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

M. B. Sletfjerding· 3 shared N. S. Hatzakis· 3 shared J. Thomsen· 2 shared M. G. Malle· 2 shared A. V. Pandey· 1 shared B. L. Moller· 1 shared B. Paul· 1 shared C. C. Hansen· 1 shared

Activity by Year

2020-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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3 shared papersBiophysics

M. B. Sletfjerding

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Author profile →

3 papers

Recent·Most cited

Single particle combinatorial multiplexed liposome fusion mediated by DNA

M. G. Malle, P. M. G. Loffler, S. S.-R. Bohr, M. B. Sletfjerding, N. A. Risgaard, S. B. Jensen, M. Zhang, P. Hedegaard, S. Vogel, N. S. Hatzakis

The paper introduces SPARCLD, a method for parallelized, multi-step liposome fusion using DNA, enabling high-throughput combinatorial screening with minimal material.

bioRxiv · Jan 19, 2021Biophysics

Across kingdom biased CYP-mediated metabolism via small-molecule ligands docking on P450 oxidoreductase

S. B. Jensen, S. Thodberg, S. Parween, M. E. Moses, C. C. Hansen, J. Thomsen, M. B. Sletfjerding, C. Knudsen, R. D. Giudice, P. M. Lund, P. R. Castano, Y. G. Bustamante, F. S. Jorgensen, A. V. Pandey, T. Laursen, , N. S. Hatzakis

The paper identifies ligands that dock on P450 oxidoreductase (POR) to bias its specificity towards CYP redox partners, revealing a mechanism for pathway-specific metabolism.

bioRxiv · Sep 23, 2020 · PreprintBiophysics

DeepFRET: Rapid and automated single molecule FRET data classification using deep learning

J. Thomsen, M. B. Sletfjerding, S. Stella, B. Paul, S. B. Jensen, M. G. Malle, T. Petersen, G. Montoya, N. S. Hatzakis

DeepFRET automates smFRET data classification using deep learning, achieving >95% accuracy and speed compared to human operators.

bioRxiv · Jun 26, 2020Biophysics