SynBot: An open-source image analysis software for automated quantification of synapses.
| Autor: | Savage JT; Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA., Ramirez J; Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA., Risher WC; Department of Biomedical Sciences, Joan C. Edwards School of Medicine at Marshall University,Huntington, WV 25755, USA., Wang Y; Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA 22203, USA., Irala D; Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA., Eroglu C; Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA.; Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA.; Howard Hughes Medical Institute, Duke University Medical Center, Durham, NC 27710, USA.; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815.; Lead contact. |
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| Jazyk: | angličtina |
| Zdroj: | BioRxiv : the preprint server for biology [bioRxiv] 2024 Jul 12. Date of Electronic Publication: 2024 Jul 12. |
| DOI: | 10.1101/2023.06.26.546578 |
| Abstrakt: | The formation of precise numbers of neuronal connections, known as synapses, is crucial for brain function. Therefore, synaptogenesis mechanisms have been one of the main focuses of neuroscience. Immunohistochemistry is a common tool for visualizing synapses. Thus, quantifying the numbers of synapses from light microscopy images enables screening the impacts of experimental manipulations on synapse development. Despite its utility, this approach is paired with low throughput analysis methods that are challenging to learn and results are variable between experimenters, especially when analyzing noisy images of brain tissue. We developed an open-source ImageJ-based software, SynBot, to address these technical bottlenecks by automating the analysis. SynBot incorporates the advanced algorithms ilastik and SynQuant for accurate thresholding for synaptic puncta identification, and the code can easily be modified by users. The use of this software will allow for rapid and reproducible screening of synaptic phenotypes in healthy and diseased nervous systems. Competing Interests: Declaration of Interests The authors declare no competing interests. |
| Databáze: | MEDLINE |
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