Fluorescent microscope imaging technologies have developed at a rapid pace in recent years. High-throughput 2D fluorescent imaging platforms are now in wide use and are being applied on a proteome wide scale. Multiple fluorophore 3D imaging of live cells is being used to give detailed localization and subcellular structure information. Further, 2D and 3D video microscopy are giving important insights into the dynamics of protein localization and transport. In parallel with these developments, significant research has gone into developing new methodologies for quantifying and extracting meaning from the imaging data.
Provides an implementation of the fluorosequencing concept. Fluorosequencing Image Analysis was developed by labeling and discriminating peptides and simple peptide mixtures. It permits users to obtain sparse amino acid–sequence information for individual protein molecules for thousands to millions of molecules in parallel. This method was tested on synthetic and naturally derived peptide molecules in zeptomole-scale quantities.
Analyzes, processes and visualizes multi-dimensional microscopy images. BioImageXD puts open-source computer science tools for three-dimensional visualization and analysis into the hands of all researchers, through a user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses or undisclosed algorithms and enables publication of precise, reproducible and modifiable workflows. It allows simple construction of processing pipelines and should enable biologists to perform challenging analyses of complex processes.
An open source application for the visualization and analysis of 4D biological datasets. Developed by researchers, it is primarily used for the analysis and quantification of 4D live-imaged confocal data. The software's modular design makes it easy to include existing libraries, or to implement new algorithms. Cell geometries extracted with MorphoGraphX can be exported and used as templates for simulation models, providing a powerful platform to investigate the interactions between shape, genes and growth.
A tool for segmentation, fluorescence quantification, and tracking of cells on microscopy images. CellX decodes the information across the cell membrane and guarantees optimal detection of the cell boundaries on a per-cell basis. Graph cuts account for the information of the cell boundaries through directional cross-correlations, and they automatically incorporate spatial constraints. The method accurately segments images of various cell types grown in dense cultures that are acquired with different microscopy techniques.
Detects statistically robust phenotypic differences. MiCASA is an unbiased, user-independent method for identifying the phenotypic differences between conditions. It focuses attention on those aspects of the phenotype that have statistical relevance. This package may be used to provide a useful summary of the distribution and interactions between well-known cell types in the thymus. However, MiCASA can be used with any pair of markers.
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