Author

D. M. Presman

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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Research Focus:cell signaling & trafficking· 3 Approach:experimental assay· 2 Research Focus:cell type annotation· 1 Assay:ChIP-seq· 1 Research Focus:chromatin & epigenetic regulation· 1 Assay:fluorescence / live-cell microscopy· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

G. Fettweis· 3 shared G. L. Hager· 3 shared A. Upadhyaya· 2 shared V. Paakinaho· 2 shared B. Almeida-Prieto· 1 shared C. Jarzynski· 1 shared D. A. Garcia· 1 shared D. A. Stavreva· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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3 shared papersBiophysics

G. Fettweis

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

The mineralocorticoid receptor forms higher order oligomers upon DNA binding

G. Fettweis, T. A. Johnson, B. Almeida-Prieto, D. M. Presman, G. L. Hager, D. Alvarez de la Rosa

This study shows that the mineralocorticoid receptor (MR) forms tetramers in the nucleoplasm and higher order oligomers upon DNA binding, differing from the glucocorticoid receptor (GR) in quaternary structure.

bioRxiv · Jan 26, 2023Biophysics

Single-molecule tracking reveals two low-mobility states for chromatin and transcriptional regulators within the nucleus

K. Wagh, D. A. Stavreva, R. A. Jensen, V. Paakinaho, G. Fettweis, R. L. Schiltz, D. Wüstner, S. Mandrup, D. M. Presman, A. Upadhyaya, G. L. Hager

This study uses single-molecule tracking and machine learning to identify two low-mobility states of chromatin and transcriptional regulators, showing dynamic interactions and switching between states.

bioRxiv · Jul 25, 2022Biophysics

Power-law behaviour of transcription factor dynamics at the single-molecule level implies a continuum affinity model

D. A. Garcia, G. Fettweis, D. M. Presman, V. Paakinaho, C. Jarzynski, A. Upadhyaya, G. L. Hager

The paper analyzes single-molecule tracking data of transcription factors and finds power-law distributions, suggesting a continuum affinity model rather than discrete binding states.

bioRxiv · Oct 8, 2020Biophysics