MathWorks. MatLAB Bioinformatics Toolbox User's Guide R2020a

Authors not specified. — The MathWorks, Inc., 2020. — 228 p.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.Computational biologists use MathWorks products to understand and predict biological behavior using data analysis and mathematical modeling.MathWorks products provide a single, integrated environment to support pharmacokinetics (PK), bioinformatics, systems biology, bioimage processing, and biostatistics.You can use MathWorks computational biology products to:
- Import, analyze, and model data, and share results
- Automate workflow elements
- Customize algorithms and tools critical to developing innovative methods for working with unexplored research areas
- Leverage proven, commercially supported algorithms and toolsGetting Started
High-Throughput Sequence Analysis
Sequence Analysis
Microarray Analysis
Phylogenetic Analysis