Kyle Karhohs, Ph.D.
Affiliations: | 2016-2018 | Imaging Platform | Broad Institute of MIT and Harvard, USA |
Area:
Cell Biology, Tissue Biology, Assay developmentGoogle:
"Kyle Karhohs"
BETA: Related publications
See more...
Publications
|
You can help our author matching system! If you notice any publications incorrectly attributed to this author, please sign in and mark matches as correct or incorrect. |
| Berryer MH, Rizki G, Nathanson A, et al. (2023) High-content synaptic phenotyping in human cellular models reveals a role for BET proteins in synapse assembly. Elife. 12 |
| Way GP, Natoli T, Adeboye A, et al. (2022) Morphology and gene expression profiling provide complementary information for mapping cell state. Cell Systems. 13: 911-923.e9 |
| Boivin B, Roet KCD, Huang X, et al. (2021) A Multiparametric Activity Profiling Platform for Neuron Disease Phenotyping and Drug Screening. Molecular Biology of the Cell. mbcE21100481 |
| Taga M, Petyuk VA, White C, et al. (2020) BIN1 protein isoforms are differentially expressed in astrocytes, neurons, and microglia: neuronal and astrocyte BIN1 are implicated in tau pathology. Molecular Neurodegeneration. 15: 44 |
| French SL, Vijey P, Karhohs KW, et al. (2020) High Content, Label-Free Analysis of Proplatelet Production from Megakaryocytes. Journal of Thrombosis and Haemostasis : Jth |
| Caicedo JC, Goodman A, Karhohs KW, et al. (2020) Publisher Correction: Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl. Nature Methods |
| Lee CX, Cheah JH, Soule CK, et al. (2019) Identification and local delivery of vasodilators for the reduction of ureteral contractions. Nature Biomedical Engineering |
| Caicedo JC, Goodman A, Karhohs KW, et al. (2019) Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl. Nature Methods |
| Shlevkov E, Basu H, Bray MA, et al. (2019) A High-Content Screen Identifies TPP1 and Aurora B as Regulators of Axonal Mitochondrial Transport. Cell Reports. 28: 3224-3237.e5 |
| Caicedo JC, Roth J, Goodman A, et al. (2019) Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images. Cytometry. Part a : the Journal of the International Society For Analytical Cytology |