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Massachusetts Institute of Technology Integrates Cancer Research in the Lab and Classroom with MathW

"Researchers are typically interested in results, not programming. MATLAB enables us to think at a higher level of abstraction and spend less time developing, debugging, testing, and creating graphs. As a result, we get research results much faster." - Dr.Gil Alterovitz, Massachusetts Institute of Technology and Harvard University

Bioinformatics Toolbox

Read, analyze, and visualize genomic, proteomic, and microarray data

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NGS browser (top), circular DNA map (bottom), and secondary structure of RNA sequence (left). Bioinformatics Toolbox includes a variety of tools for visualizing sequence data.

 

Bioinformatics Toolbox™ provides algorithms and visualization techniques for Next Generation Sequencing (NGS), microarray analysis, mass spectrometry, and gene ontology. Using toolbox functions, you can read genomic and proteomic data from standard file formats such as SAM, FASTA, CEL, and CDF, as well as from online databases such as the NCBI Gene Expression Omnibus and GenBank®. You can explore and visualize this data with sequence browsers, spatial heatmaps, and clustergrams. The toolbox also provides statistical techniques for detecting peaks, imputing values for missing data, and selecting features.

You can combine toolbox functions to support common bioinformatics workflows. You can use ChIP-Seq data to identify transcription factors; analyze RNA-Seq data to identify differentially expressed genes; identify copy number variants and SNPs in microarray data; and classify protein profiles using mass spectrometry data.

Learn more about computational biology.

 

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