Tuesday, November 23, 2004

Bioinformatics 2.0 for MathLab

The MathWorks just released version 2.0 of their MATLAB Bioinformatics ToolBox. Its a set of bioinformatics-related functions allowing to do various tasks, ranging from microarray data normalization, visualization and analysis, protein, DNA and RNA sequence analysis, phylogeny, data retrieval from the web databases, etc. Its similar to Accelrys GCG Wisconsin package, but a few key differences should be noted.

First of all, functions are implemented in MATLAB language, are open source and customizable. The MATLAB environment also allow you to develop (and share) your own algorithms. It offers advanced machine (vector-based) learning options, mass spectrometry and microarray analysis. The full list of functions can be found here. Note that it isn't free (prices start from $1000 US), but a demo is available. It is available for Windows, UNIX/Linux and Mac platforms. Since some people getting into bioinformatics come from an engineer/math background, the opportunity to develop and work in a MATLAB environment is interesting. Excerpt from the press release :

New Toolbox Features Mass-Spectrometry and Statistical Inference and
Prediction Capabilities That Enable Faster and More Customized Analysis of

Addressing the needs of computational biologists and bioinformatists, The MathWorks today announced the availability of the Bioinformatics Toolbox 2.0 for MATLAB(R). 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. [...]

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. [...]

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. [...]

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. [...]

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