Read, analyze, and visualize genomic and proteomic data
About Matlab Bioinformatics Toolbox
Bioinformatics Toolbox™ provides algorithms and apps 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.
- Getting Started
Learn the basics of Bioinformatics Toolbox
- High-Throughput Sequencing
Gene expression, transcription factor, and methylation analysis of Next-Generation Sequencing (NGS) data, including RNA-Seq and ChIP-Seq
- Microarray Analysis
Gene expression and genetic variant analysis of microarray data
- Sequence Analysis
Genomic and proteomic sequences, alignment, and phylogenetics
- Structural Analysis
Visualize and manipulate 3-D structures of proteins and other biomolecules; RNA secondary structure prediction and visualization
- Mass Spectrometry and Bioanalytics
Data from separation techniques that produce traces with peaks, including MS, LC/MS, NMR, chromatography, and electrophoresis