Bioinformatics Toolbox™ 3.1

Product Description

• Bioinformatics Toolbox Key Features
• Microarray Data Analysis and Visualization
• Mass Spectrometry Data Analysis
• Graph Theory, Statistical Learning, and Gene Ontology
• Sequence Analysis
• Importing Data and Deploying Applications

File Formats and Database Access

You can access many standard file formats for biological data, Web-based databases, and other online data sources from Bioinformatics Toolbox. For example, you can:

• Read sequence data from standard file formats, including FASTA, PDB, and SCF
• Read microarray data from file formats such as Affymetrix DAT, EXP, CEL, CHP, and CDF files; ImaGene results format data; Agilent Feature Extraction Software files; and GenePix GPR and GAL files
• Interface with major Web-based databases, such as GenBank, EMBL, NCBI BLAST, and PDB
• Import data directly from the NCBI Gene Expression Omnibus Web site using a single command
• Read cytogenetic banding information from NCBI ideograms or UCSC cytoband text files
• Read mass spectrometry data from MZXML and JCAMP-DX files

Sharing Algorithms and Deploying Applications
with Bioinformatics Toolbox and MATLAB

MATLAB includes tools that let you turn your data analysis program into a customized software application. These include an interactive GUI builder; programming tools, such as a visual debugger for algorithm development and refinement; and an algorithm performance profiler to accelerate development. You can share data analysis algorithms created in the MATLAB language across all platforms supported by MATLAB.

Tutorial examples show how to integrate MATLAB with commonly used bioinformatics tools, such as Bio Perl, SOAP-based Web services, and COM plug-ins. Using MATLAB application deployment products (available separately), you can integrate your MATLAB algorithms with existing C, C++, and Java applications, deploy the developed algorithms and GUIs as stand-alone applications, convert MATLAB algorithms into Microsoft .NET or COM components that can be accessed from any COM-based application, and create Microsoft Excel® add-ins.

Scatter plot of microarray data showing significance versus gene expression ratio. Click on image to see enlarged view.