Read and perform basic operations with data produced by the Illumina/Solexa Genome Analyzer®.
Perform a genome-wide analysis of a transcription factor in the Arabidopsis Thaliana (Thale Cress) model organism.
An analysis of the origin and diffusion of the SARS epidemic. It is based on the discussion of viral phylogeny presented in Chapter 7 of "Introduction to Computational Genomics. A Case
Construct phylogenetic trees from multiple strains of the HIV and SIV viruses.
How the analysis of synonymous and nonsynonymous mutations at the nucleotide level can suggest patterns of molecular adaptation in the genome of HIV-1. This example is based on the
The interoperability between MATLAB® and Bioperl - passing arguments from MATLAB to Perl scripts and pulling BLAST search data back to MATLAB.
Extract some sequences from GenBank®, find open reading frames (ORFs), and then aligns the sequences using global and local alignment algorithms.
Programmatically search and retrieve data from NCBI's Entrez databases using NCBI's Entrez Utilities (E-Utilities).
Construct phylogenetic trees from mtDNA sequences for the Hominidae taxa (also known as pongidae). This family embraces the gorillas, chimpanzees, orangutans and humans.
Calculate Ka/Ks ratios for eight genes in the H5N1 and H2N3 virus genomes, and perform a phylogenetic analysis on the HA gene from H5N1 virus isolated from chickens across Africa and Asia. For
Basic sequence manipulation techniques and computes some useful sequence statistics. It also illustrates how to look for coding regions (such as proteins) and pursue further analysis of
Illustrates a simple metagenomic analysis on a sample data set from the Sargasso Sea. It requires the taxonomy information included in the files gi_taxid_prot.dmp, names.dmp and
How HMM profiles are used to characterize protein families. Profile analysis is a key tool in bioinformatics. The common pairwise comparison methods are usually not sensitive and specific
Use the Bioinformatics Toolbox™ to find potential primers that can be used for automated DNA sequencing.
Illustrates a simple approach to searching for potential regulatory motifs in a set of co-expressed genomic sequences by identifying significantly over-represented ungapped words of
A method that can be used to investigate the significance of sequence alignments. The number of identities or positives in an alignment is not a clear indicator of a significant alignment. A
Analyze Illumina BeadChip gene expression summary data using MATLAB® and Bioinformatics Toolbox™ functions.
Use the BIOGRAPH object to visually represent interconnected data.
Create and manipulate MATLAB® containers designed for storing data from a microarray experiment.
Detect DNA copy number alterations in genome-wide array-based comparative genomic hybridization (CGH) data.
Retrieve gene expression data series (GSE) from the NCBI Gene Expression Omnibus (GEO) and perform basic analysis on the expression profiles.
Enrich microarray gene expression data using the Gene Ontology relationships.
How Bioinformatics Toolbox™ can be used to work with and visualize graphs.
Identify differentially expressed genes from microarray data and uses Gene Ontology to determine significant biological functions that are associated to the down- and up-regulated
Use a Bayesian hidden Markov model (HMM) technique to identify copy number alteration in array-based comparative genomic hybridization (CGH) data.
Use MATLAB® and Bioinformatics Toolbox™ for preprocessing Affymetrix® oligonucleotide microarray probe-level data with two preprocessing techniques, Robust Multi-array Average
Various ways to explore and visualize raw microarray data. The example uses microarray data from a study of gene expression in mouse brains .
Use the functions in the Bioinformatics Toolbox™ for working with Affymetrix® GeneChip® data.
Classify mass spectrometry data and shows some statistical tools that can be used to look for potential disease markers and proteomic pattern diagnostics.
How the SAMPLEALIGN function can correct nonlinear warping in the chromatographic dimension of hyphenated mass spectrometry data sets without the need for full identification of the
Manipulate, preprocess and visualize data from Liquid Chromatography coupled with Mass Spectrometry (LC/MS). These large and high dimensional data sets are extensively utilized in
Use a single computer, a multicore computer, or a cluster of computers to preprocess a large set of mass spectrometry signals. Note: Parallel Computing Toolbox™ and MATLAB® Distributed
Improve the quality of raw mass spectrometry data. In particular, this example illustrates the typical steps for preprocesssing protein surface-enhanced laser
Compare whole genomes for organisms, which allows you to compare the organisms at a very different resolution relative to single gene comparisons. Instead of just focusing on the
Create a memory mapped file for sequence data and work with it without loading all the genomic sequence into memory. Whole genomes are available for human, mouse, rat, fugu, and several other
A secondary structure prediction method that uses a feed-forward neural network and the functionality available with the Deep Learning Toolbox™.