Susanne M Rafelski
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Explore the profile of Susanne M Rafelski including associated specialties, affiliations and a list of published articles.
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33
Citations
1852
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Recent Articles
1.
Interpretable representation learning for 3D multi-piece intracellular structures using point clouds
Vasan R, Ferrante A, Borensztejn A, Frick C, Gaudreault N, Mogre S, et al.
bioRxiv
. 2024 Aug;
PMID: 39091871
A key challenge in understanding subcellular organization is quantifying interpretable measurements of intracellular structures with complex multi-piece morphologies in an objective, robust and generalizable manner. Here we introduce a morphology-appropriate...
2.
Dixon J, Frick C, Leveille C, Garrison P, Lee P, Mogre S, et al.
bioRxiv
. 2024 Jul;
PMID: 38979140
To investigate the fundamental question of how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we focused on nuclear growth in hiPS cell colonies as...
3.
Rafelski S, Theriot J
Cell
. 2024 May;
187(11):2633-2651.
PMID: 38788687
Cell states were traditionally defined by how they looked, where they were located, and what functions they performed. In this post-genomic era, the field is largely focused on a molecular...
4.
Reinke A, Tizabi M, Baumgartner M, Eisenmann M, Heckmann-Notzel D, Kavur A, et al.
Nat Methods
. 2024 Feb;
21(2):182-194.
PMID: 38347140
Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image...
5.
Gregor B, Coston M, Adams E, Arakaki J, Borensztejn A, Do T, et al.
Nat Protoc
. 2023 Dec;
19(2):565-594.
PMID: 38087082
To produce abundant cell culture samples to generate large, standardized image datasets of human induced pluripotent stem (hiPS) cells, we developed an automated workflow on a Hamilton STAR liquid handler...
6.
Chen J, Viana M, Rafelski S
Nat Methods
. 2023 Jul;
20(7):968-970.
PMID: 37433995
No abstract available.
7.
Dekker J, Alber F, Aufmkolk S, Beliveau B, Bruneau B, Belmont A, et al.
Mol Cell
. 2023 Jul;
83(15):2624-2640.
PMID: 37419111
The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies...
8.
Reinke A, Tizabi M, Baumgartner M, Eisenmann M, Heckmann-Notzel D, Kavur A, et al.
ArXiv
. 2023 Mar;
PMID: 36945687
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence...
9.
Viana M, Chen J, Knijnenburg T, Vasan R, Yan C, Arakaki J, et al.
Nature
. 2023 Jan;
613(7943):345-354.
PMID: 36599983
Understanding how a subset of expressed genes dictates cellular phenotype is a considerable challenge owing to the large numbers of molecules involved, their combinatorics and the plethora of cellular behaviours...
10.
Gerbin K, Grancharova T, Donovan-Maiye R, Hendershott M, Anderson H, Brown J, et al.
Cell Syst
. 2021 May;
12(6):670-687.e10.
PMID: 34043964
Although some cell types may be defined anatomically or by physiological function, a rigorous definition of cell state remains elusive. Here, we develop a quantitative, imaging-based platform for the systematic...