I’ve been fascinated by genomic research for years. While successfully implementing a fairly large and diverse set of algorithms (segmentation, image processing and machine learning) on text, image and other semi-structured datasets, till recently I didn’t have much exposure to the exciting field of bioinformatics, processing DNA and RNA sequences.
After completing Bioinformatics Methods I and Bioinformatics Methods II (thank you Professor Nicholas Provart, University of Toronto) I have a better appreciation of the important roles of Bioinformatics in medicinal sciences and in drug discovery, diagnosis and disease management, but also a better appreciation of the complexity involved with the processing of large biological datasets.
Topics covered in these two courses include multiple sequence alignments, phylogenetics, gene expression data analysis, and protein interaction networks, in two separate parts. The first part, Bioinformatic Methods I, dealt with databases, Blast, multiple sequence alignments, phylogenetics, selection analysis and metagenomics. The second part, Bioinformatic Methods II, dealt with motif searching, protein-protein interactions, structural bioinformatics, gene expression data analysis, and cis-element predictions.
Please find below a short list of tools and resources I’ve used while completing the different labs:
Multiple Sequence Alignments
http://megasoftware.net (download tool)
NEXT GENERATION SEQUENCING APPLICATIONS: RNA-SEQ AND METAGENOMICS
Protein Domain, Motif and Profile Analysis
http://www.cytoscape.org/download.html (download tool)
http://pymol.org/edu (download tool)
Gene Expression Analysis
Gene Expression Data Analysis
Cis regulatory element mapping and prediction
https://class.coursera.org/molevol-002 Computational Molecular Evolution
https://www.coursera.org/course/webapplications Web Applications (Ruby on Rails)
https://www.coursera.org/course/genomicmedicine Genomic & Precision Medicine
https://www.coursera.org/course/usefulgenetics Useful Genetics
Zvelebil & Baum 2008 Understanding Bioinformatics. Garland Science, New York