Difference between revisions of "Applied Bioinformatics Main Page"

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Latest revision as of 16:38, 1 May 2017

Applied Bioinformatics

Welcome to the Applied Bioinformatics Course Wiki.

These wiki pages are provided to coordinate information, activities and projects in the applied bioinformatics courses taught by Boris Steipe at the University of Toronto. If you are not one of my students, you can still browse this site, however only users with a login account can edit or contribute or edit material. If you are here because you are interested in general aspects of bioinformatics or computational biology, you may want to review the Wikipedia article on bioinformatics, or visit Wikiomics. Contact boris.steipe(at)utoronto.ca with any questions you may have.



The Courses

This material is variably being used in my undergraduate courses BCH441 (Bioinformatics), BCB410 (Applied Bioinformatics), BCB420 (Computational Systems Biology), their graduate course cognates BCH1441 and JTB2020, and other workshops I teach.


 

Continue here for the current BCB410H course page ...


 

Continue here for guidelines on BCB330Y and BCB430Y projects with me ...


 

Topics

 

Hardware

High performance computing
Cloud computing
 

Systems and Tools

Unix
Network Configuration
Apache
MySQL
Tools for the bioinformatics lab
GBrowse and LDAS
 

Programming

Software Development (in a small-scale research context)
SPN (Structured Process Notation)
IDE (Integrated Development Environment)
Regular Expressions
Screenscraping
Perl
BioPerl
PHP
Data modelling
BioPython
Graphical output
Autonomous agents
CVS / Git

Algorithms

General Algorithms
Optimization
 
Algorithms on Sequences
Dynamic Programming
Multiple Sequence Alignment
Genome Assembly
 
Algorithms on Structures
Docking
Protein Structure Prediction
 
Algorithms on Trees
Computing with trees
 
Algorithms on Networks
Network metrics
Dijkstras Algorithm
Floyd Warshall Algorithm

Communication and collaboration

MediaWiki
HTML essentials
HTML 5
CSS
SADI and SHARE - a Semantic Web Service framework
CGI
 

Statistics

Pattern discovery
Correlation
Clustering methods
Cluster quality metrics
The Map Equation
Machine learning
Information theory
R
Introductory tutorial to R
R plotting
R programming
R EDA
R regression
R PCA
R Clustering
R Gene expression clustering
R Classification
R hypothesis testing
Bioconductor
Regular Expressions
Bayesian inference
 

Applications

BLAST scripting
Chimera programming
Biological data access and integration
Text mining
HMMER
High-throughput sequencing
Functional annotation
Microarray analysis
 


Resources

Course related


Contents related