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Addressing the needs of computational biologists and bioinformatists, The MathWorks today announced the availability of the Bioinformatics Toolbox 2.0 for MATLAB. Scientists and researchers can now perform mass-spectrometry data analysis, perform statistical inference and prediction, view graphs, and conduct enhanced genomic and proteomic sequence analysis. With the latest release of its Bioinformatics Toolbox, The MathWorks brings greater power and versatility to the biotechnology and pharmaceutical industries, providing more advanced technology capabilities for drug discovery research, genetic engineering, and other genomics and proteomics projects. The Bioinformatics Toolbox 2.0 offers computational biologists and other research scientists an open and extensible environment. Most functions are implemented in the open MATLAB language, enabling users to customize the algorithms or develop their own. The new mass-spectrometry data analysis feature is specifically designed for pre-processing data, including baseline correction, smoothing, alignment, and re-sampling. As a result, users can now perform customized analysis at a faster rate. "We have found mass-spectrometry data analysis methods in the Bioinformatics Toolbox 2.0 allow for easier processing of data using an efficient, engineering-based approach," said Gil Alterovitz of the Massachusetts Institute of Technology and the HST-Children's Hospital Informatics Program. "Previously, we were required to invest extensive time creating this capability in-house but through collaborative efforts with The MathWorks, we have found them very responsive to customer needs. As a result, the Bioinformatics Toolbox new algorithms have increased our productivity." The Bioinformatics Toolbox 2.0 also builds on the classification and statistical inference and prediction tools in the Statistics Toolbox by providing several new classification functions and tools for identification of discriminating features, and visualization of complex data is enhanced with new graph-viewing functions and manipulation tools that display interaction maps, hierarchy plots, and pathways. Additional features of the Bioinformatics Toolbox 2.0 provide access to specialized visualization tools, ranging from sequence alignments and microarray principle component plots to building and interactively viewing and manipulating phylogenetic trees. "The Bioinformatics Toolbox 2.0 enables users to gain a better understanding of data while supporting their efforts to generate cutting-edge advancements in their fields," said Kristen Amuzzini, biotechnology and pharmaceutical industry marketing manager, The MathWorks. "The complex functions such as mass-spectrometry data analysis and statistical inference and prediction mean that professionals in this industry can now easily explore ideas, prototype new algorithms, and build better applications for their projects." In an effort to bring computational biologists, bioinformatists, and other technical professionals the power and performance they demand in their applications, The MathWorks recently released the Distributed Computing Toolbox, which enables users to execute MATLAB algorithms in a cluster of computers. Using the Distributed Computing Toolbox with the Bioinformatics Toolbox, scientists can perform intensive computations with large data sets previously unattainable on a single computer for applications such as genomic and proteomic sequence and microarray analysis.