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Computational Tools in Biology: a hands on course
January 11 - 15
Coordination: Rui Travasso, Physics Department, UC
Computational Tools in Biology: a hands on course
January 11- 15, 2016,

The course will be held at Physics Department, Room D6 (1st floor).

Classes start from 09: 00h to 13: 00h.
There will be a break in mid-morning.


•    Increase the student´s familiarity with techniques of analysing and modelling biological systems using the computer

•    Introduce the student to computer programming and to debug her/his own code through a hands-on approach

•    Introduction to computational modelling and data treatment in biology.

•    Introduce some image processing operators through case-based instruction

Introduction to Programming
Rui Travasso

•    Why to use a computer. Basic notions of programming. Uses and limitations of a computer.

•    Introduction to the MatLab environment: variables, matrices, and operations in Matlab.
Graphical representation of data.

•    Cycles and conditions in MatLab. Using and building external functions.

•    Examples

Overview of Modelling in Biology

Rui Travasso

•    Examples of using the computer to model Biological Systems.
     - Modelling of biological molecules: Computational Structural Biology
     - Chemotaxis and adhesion: Multi-scale models in Biology

Computational Tools in Bioinformatics
Joel Arrais

•    Overview of the Matlab Bioinformatics package, organization and common functions

•    Guided examples of biological data analysis:
     - Sequence analysis and visualization, including pairwise alignment
     - Microarray data analysis pipeline, including normalizing, and visualization
     - Functional analysis including interaction graphs, hierarchical plots, and pathways

•    Practice: Hands-on exercises based on example problems.

Computational Tools in Image Analysis
Luís Cruz

•    Brief overview of the Matlab image processing pipeline, common functions and operators
•    Tutorial: Step-by-step solution of some biomedical image processing problems
•    Review and additional information on Matlab image processing functions
•    Practice: Hands-on exercises based on example problems.
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