Post secondary educational courses and training

As complements to the ISB-offered Introduction to Systems Biology and Proteomics courses, the Center has developed three courses for interdisciplinary education and training in:

Introductions to Experimental and Computational Biology. This course is intended to introduce concepts and approaches in computational biology to experimentalists as well as fundamental ideas and techniques in molecular and cellular biology to computational scientists. Objectives of this course are to further encourage multidisciplinary interactions and to stimulate new ideas for collaborations and encourage a greater appreciation of the capabilities and limitations of mathematical and computational analysis as well as experimental techniques.

Microfluidics. This course aims to eliminate two barriers which exist for groups wishing to integrate MSL technology into their programs: 1) the initial acquisition of the required design, fabrication, and operations skills, and 2) the need for ongoing interaction with other researchers in order to refine designs and techniques, and to disseminate solutions to common problems in the application of this technology to bioassays. In 2008, the Microfluidics course will teach the elements for microfluidic device theory, design, fabrication, and operation in biological experiments. The course will be aimed at practicing researchers, as well as graduate students in both the biological and the physical sciences.

Network Analysis. The objective of this course is to convey topics pertaining to the modeling, inference, and simulation of biomolecular networks in a manner accessible to non-computational biologists. The course will give an overview of the various modeling formalisms, including graph-based models, discrete dynamical systems, probabilistic and stochastic model classes, and continuous modeling approaches. These topics will be presented in the context of the types of analysis undertaken as well as the kinds of measurements available. Various approaches for inferring network models, including data integration methodologies, will be covered. The simulation of these models aimed at predicting system behavior will be introduced and demonstrated using a variety of experimental systems studied at the ISB. Finally, the course participants will be introduced to several software tools that enable modeling, analysis, and visualization of networks.