Bioinformatics

Recommended Prerequisites

- Celland molecular biology.

- Biostatistics.

Teaching Methods

The course is divided in to expository and laboratory classes. The first is dedicated to present the contentin a more theoretical approach, without failing to include the active participation of students. The aimis to develop their’s reasoning ability and integration of knowledge and stimulate their critical thinking. Practical classes will enable the student to explore the acquired concepts. Those will follow a problem oriented approach by launching challenges that require knowledge integration, and where verpossible, the use of working groups and discussion.

The evaluation is base dont he realization of a written exam that will evaluatet he knowledge obtained in class (40% of final grade) and the evaluation of their performance during the Pratical classes (60% of final grade).

Learning Outcomes

Systematic comprehension on of the main algorithm sand too lsusedin Bioinformatics. In particular, it is aim to focus on method so analysis and annotation of sequences, application algorithms in proteomics and in the area of systems biology, and especially in genomic regulatory networks.

Work Placement(s)

No

Head Lecturer(s)

Nuno António Marques Lourenço

Assessment Methods

Assessment
Exam: 40.0%
Laboratory work or Field work: 60.0%

Bibliography

Gusfield, Dan. AlgorithmsonStrings, TreesandSequences: ComputerScienceandComputationalBiology. Cambridge, UK: Cambridge UniversityPress, 1997. ISBN: 0521585198.

Waterman, Michael. Introduction to ComputationalBiology: Maps, Sequences, andGenomes. Boca Raton, FL: CRC Press, 1995. ISBN: 0412993910.

Durbin, Richard, GraemeMitchison, S. Eddy, A. Krogh, and G. Mitchison. BiologicalSequenceAnalysis: ProbabilisticModelsofProteinsandNucleicAcids. Cambridge, UK: Cambridge UniversityPress, 1997. ISBN: 0521629713.

Jones, Neil, and Pavel Pevzner. AnIntroduction to BioinformaticsAlgorithms. Cambridge, MA: MIT Press , 2004. ISBN: 0262101068.