Data visualization image visualizations

The data can be visualized in several formats. In a gel image, the optical density at each point is related to the fluorescence intensity false color images can be used to improve the dynamic range of visualization. We usually employ a logarithmic compression to help visualize the wide dynamic range of the data the image can be processed to saturate the most intense components, allowing observation of less intense components. 

CellProfiler and CellProfiler Analyst are free Open Source software for automated image analysis, data visualization, and machine learning. Versions for Mac, Windows, and Linux are available and both software can be downloaded at http //www.cellprofiler. org. CellProfiler was developed by Anne Carpenter and Thouis Jones in the laboratory of David Sabatini at the Whitehead Institute for Biomedical Research and by Polina Golland at the CSAIL of the MIT. 

Bioinformatics Robotics control, image processing, data mining, and visualization are usually used for implementation of microarray experiments. 

Chemical image data sets are visualized as a three-dimensional cube spanning one wavelength and two spatial dimensions called a hypercube (Figure 7.2). Each element within the cube contains the intensity-response information measured at that spatial and spectral index. The hypercube can be treated as a series of spatially resolved spectra (called... 

Spectroscopic imaging data are frequently visualized as metabolite maps, i.e. for each metabolite the concentration is displayed either as a gray image or... 

At the most basic level, the data can be visualized (rendered) as an image volume viewed at varying angles and manually compressed or stretched to fit. Alternatively, a more mathematical approach can be taken if the optical aberrations can be measured. In 3D fluorescence microscopy, this measurement is known as the point spread function (psf), and a process of deconvolution can be used to correct any aberrations with a known psf. Once corrected, the data can be rendered for viewing and measurement with confidence. 

The visual image collection via a CCD camera was completely integrated with the microscope stage motion and IR spectra data acquisition. 

Figure 8.25. In image analysis, a flat image has two pixel indices and time or wavelength as a third way to form three-way arrays. By using volumes (three voxel indices) measured at different wavelengths and at different times five-way arrays can be produced. The visualization is special since the raw data are images and many model parameters and residuals can be visualized as images.

Scientific visualization deals with visualizing large data sets. Both raw, derived and calculated data can be visualized. Large systems such as weather data (real data) and results of aerodynamic calculations (calculated data) are used frequently [Nielson et al. 1990, Jones 1996, Cleveland 1985, Cleveland McGill 1988], Scientific visualization uses images, color, volume rendering by interpolation, special symbols and animation. Sound is also included if appropriate. In this book, color is not used and animation is impossible with static figures, but they certainly have a future for visualization in three-way analysis. 

Fig. 3. Data from a 2-D difference gel electrophoresis (DICE) experiment can be viewed in a number of ways in DeCyder 2-D, including 2-D spot maps, 3-D images visualizing specific spot intensities, and graphical depiction comparing the abundance of each matched spot across the samples in the experiment. This experiment compared lung tissue (universal control, UC) against tissue exposed to smoke (Smoke) and tissue exposed to smoke in the presence of an inhibitor (Ini or In2). All possible t-test and average ratio values can be calculated very easily as shown for this spot. Unpublished data from samples kindly provided by Dr. Koustubh Panda, Cleveland Clinic Foundation.

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