Cargando…
Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene expression in the developing C. elegans embryo
BACKGROUND: Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tracking the expression of individual C. elegans genes was developed that collects image samples of a developing embryo by...
Autores principales: | Aydin, Zafer, Murray, John I, Waterston, Robert H, Noble, William S |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2010
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2838868/ https://www.ncbi.nlm.nih.gov/pubmed/20146825 http://dx.doi.org/10.1186/1471-2105-11-84 |
Ejemplares similares
-
Multidimensional regulation of gene expression in the C. elegans embryo
por: Murray, John Isaac, et al.
Publicado: (2012) -
Improving the Caenorhabditis elegans Genome Annotation Using Machine Learning
por: Rätsch, Gunnar, et al.
Publicado: (2007) -
A deep learning segmentation strategy that minimizes the amount of manually annotated images
por: Pécot, Thierry, et al.
Publicado: (2022) -
Automated cellular annotation for high-resolution images of adult Caenorhabditis elegans
por: Aerni, Sarah J., et al.
Publicado: (2013) -
Visual Image Annotation for Bowel Obstruction: Repeatability and Agreement with Manual Annotation and Neural Networks
por: Murphy, Paul M.
Publicado: (2023)