Data visualization

Data visualization is the process of displaying information in any sort of pictorial or graphic representation. A number of computer programs are available to apply a colorization scheme to data or to work with three-dimensional representations. In recent years, this functionality has been incorporated in many... 

The results of CFD packages are obtained by several means, due to the versatile data visualization tools that are now incorporated in many workstations. The results can be of several forms ... 

The described computational tools provide interactive, fast, and flexible data visualizations of chemical data that help and even enhance the human thought processes. However, visualization alone is often inadequate when multiple data points must be considered. A number of data mining methods that seek to identify significant relationships in large multidimensional databases are now being used for library design. 

This is meant schematically modem MCA modules usually do not have a screen but are controlled by a front-end PC for parameter setting and data visualization. 

Matlab - high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis and numerical computation (http / /www. math works. com/)... 

Buja A, Cook D, Swayne DF (1996) Interactive high-dimensional data visualization. J Computat Graph Stat 5 78... 

Such a plot identifies the nature of our data, visually classifying them into those that will not influence our analysis (in the set shown, clearly scores of 0 fit into this category) and those that will critically influence the outcome of an analysis. In so doing, the position of control ( normal ) observations is readily revealed as a central tendency in the data (hence the name for this technique). 

Sakar, D. Lattice Multivariate Data Visualization with R. Springer, New York, 2007. 

A simple spreadsheet tool can be used to capture the results of the fraction analyses, provide data visualization, integrate the responses, and thereby establish starting points for the fraction collection window(s), estimation of target purity and amount recovered. This data is useful for extrapolating the number of... 

MetaBase is a curated database of human protein-protein and protein-DNA interactions, transcriptional factors, signaling, metabolism and bioactive molecules. MetaCore provides intuitive tools for data visualization, mapping and exchange, multiple networking algorithms and data mining. 

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. 

Of course, there are limitations to this approach that must be kept in mind. First, because we use commercially available components for the data visualization, we are tied to the standard file formats. For the most part these formats are sufficient, but in certain cases they can be limiting. For example, there is no standard for handling multiple entries for a single data field. This becomes an issue when retrieving assay results, because in many cases more than one experiment has been run. Second, this system requires a robust and fast network since many file uploads and downloads to the server are involved. However, in practice we have found these issues to be manageable. 

The data on the first CD are stored in Voyager. voy files and are easily displayed using the Voyager data visualization software, also included on the CD. The... 

Applications of molecular descriptors are as diverse as their definitions. The important classes of applications include QSAR and/or QSPR, similarity, diversity, predictive models for virtual screening and/or data mining, data visualization. We will discuss briefly some of these applications in the next sections. 

Reducing the dimensionality of the descriptor space not only facilitates model building with molecular descriptors but also makes data visualization and identification of key variables in various models possible. Notice that while a low dimension mathematically simplifies a problem such as model development or data visualization, it is usually more difficult to correlate trends directly with physical descriptors, and hence the data become less interpretable, after the dimension transformation. Trends directly linked with physical descriptors provide simple guidance for molecular modifications during potency/property optimizations. 

SpotFire for data visualization and decision making http //spotfire.tibco.com/... 

Fig. 16.3. Screen shots of PGVL Hub. It has two ways to display molecules and their properties (Structural Viewer panel and Table viewer panel). It has been integrated with SpotFire for data visualization. It also has a decision maker capable of handling numerical and textual data as well as user selections by hand.

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