
Cell, Год журнала: 2024, Номер 187(23), С. 6742 - 6759.e17
Опубликована: Окт. 24, 2024
Язык: Английский
Cell, Год журнала: 2024, Номер 187(23), С. 6742 - 6759.e17
Опубликована: Окт. 24, 2024
Язык: Английский
Nature Methods, Год журнала: 2019, Номер 16(12), С. 1226 - 1232
Опубликована: Сен. 30, 2019
Язык: Английский
Процитировано
2769Nature reviews. Neuroscience, Год журнала: 2020, Номер 21(2), С. 61 - 79
Опубликована: Янв. 2, 2020
Язык: Английский
Процитировано
504Cell, Год журнала: 2018, Номер 175(3), С. 859 - 876.e33
Опубликована: Окт. 1, 2018
Язык: Английский
Процитировано
451Protein Science, Год журнала: 2020, Номер 30(1), С. 234 - 249
Опубликована: Ноя. 9, 2020
Abstract For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, resulting larger multidimensional datasets, must adapt. ImageJ is an open‐source image analysis platform that has aided researchers with a variety of applications, driven mainly by engaged collaborative user developer communities. The close collaboration between programmers users resulted adaptations accommodate new challenges address the needs ImageJ's diverse base. consists many components, some relevant primarily developers vast collection user‐centric plugins. It available forms, including widely used Fiji distribution. We refer this entire codebase community as ecosystem. Here we review core features ecosystem highlight how responded technology advancements plugins tools recent years. These been developed several areas such visualization, segmentation, tracking biological entities large, complex datasets. Moreover, capabilities deep learning are being added ImageJ, reflecting shift bioimage towards exploiting artificial intelligence. facilitated profound architectural changes brought about ImageJ2 project. Therefore, also discuss contributions enhancing processing interoperability
Язык: Английский
Процитировано
217Nature Reviews Methods Primers, Год журнала: 2021, Номер 1(1)
Опубликована: Ноя. 3, 2021
Язык: Английский
Процитировано
214Frontiers in Computer Science, Год журнала: 2022, Номер 4
Опубликована: Фев. 10, 2022
We present LABKIT, a user-friendly Fiji plugin for the segmentation of microscopy image data. It offers easy to use manual and automated routines that can be rapidly applied single- multi-channel images as well timelapse movies in 2D or 3D. LABKIT is specifically designed work efficiently on big data enables users consumer laptops conveniently with multiple-terabyte images. This efficiency achieved by using ImgLib2 BigDataViewer memory efficient fast implementation random forest based pixel classification algorithm foundation our software. Optionally we harness power graphics processing units (GPU) gain additional runtime performance. install virtually all workstations. Additionally, compatible high performance computing (HPC) clusters distributed The ability classifiers trained via ImageJ macro language integrate this functionality step workflows. Finally, comes rich online resources such tutorials examples will help familiarize themselves available features how best number practical real-world use-cases.
Язык: Английский
Процитировано
206Cell, Год журнала: 2021, Номер 184(8), С. 2084 - 2102.e19
Опубликована: Март 24, 2021
The human brain has undergone rapid expansion since humans diverged from other great apes, but the mechanism of this human-specific enlargement is still unknown. Here, we use cerebral organoids derived human, gorilla, and chimpanzee cells to study developmental mechanisms driving evolutionary expansion. We find that neuroepithelial differentiation a protracted process in involving previously unrecognized transition state characterized by change cell shape. Furthermore, show are larger due delay transition, associated with differences interkinetic nuclear migration cycle length. Comparative RNA sequencing (RNA-seq) reveals expression dynamics morphogenesis factors, including ZEB2, known epithelial-mesenchymal regulator. ZEB2 promotes its manipulation downstream signaling leads acquisition nonhuman ape architecture context vice versa, establishing an important role for shape
Язык: Английский
Процитировано
202Journal of Molecular Biology, Год журнала: 2019, Номер 431(7), С. 1315 - 1321
Опубликована: Фев. 10, 2019
Язык: Английский
Процитировано
159Nature Methods, Год журнала: 2021, Номер 19(1), С. 90 - 99
Опубликована: Дек. 30, 2021
Abstract Induced pluripotent stem cell (iPSC)-derived organoids provide models to study human organ development. Single-cell transcriptomics enable highly resolved descriptions of states within these systems; however, approaches are needed directly measure lineage relationships. Here we establish iTracer, a recorder that combines reporter barcodes with inducible CRISPR–Cas9 scarring and is compatible single-cell spatial transcriptomics. We apply iTracer explore clonality dynamics during cerebral organoid development identify time window fate restriction as well variation in neurogenic between progenitor neuron families. also long-term four-dimensional light-sheet microscopy for recording confirm regional the developing neuroepithelium. incorporate gene perturbation (iTracer-perturb) assess effect mosaic TSC2 mutations on Our data shed light how lineages fates established formation. More broadly, our techniques can be adapted any iPSC-derived culture system dissect alterations normal or perturbed
Язык: Английский
Процитировано
152International Journal of Biological Macromolecules, Год журнала: 2023, Номер 246, С. 125669 - 125669
Опубликована: Июль 4, 2023
Язык: Английский
Процитировано
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